Vehicle-side device, method, and non-transitory computer-readable storage medium for uploading map data

ABSTRACT

A method for generating or updating map data including coordinate information of a plurality of landmarks disposed along a road, includes: by a vehicle-side device, uploading index information, indicating that the map data needs to be updated to the server in associated with a road segment in which the vehicle is traveling when a predetermined event occurs in a situation where the vehicle is traveling; by the server, determining whether the map data for the road segment needs to be updated based on the index information provided by the vehicle-side device; and by a server, setting an update flag indicating that the map data needs to be updated for the road segment when determining that the map data needs to be updated.

CROSS REFERENCE TO RELATED APPLICATION

The present application is a continuation application of InternationalPatent Application No. PCT/JP2019/033208 filed on Aug. 26, 2019, whichdesignated the U.S. and claims the benefit of priority from JapanesePatent Application No. 2018-162468 filed on Aug. 31, 2018 and No.2019-143134 filed on Aug. 2, 2019. The entire disclosures of all of theabove applications are incorporated herein by reference.

TECHNICAL FIELD

The present disclosure relates to a map system, a vehicle-side device, amethod and a non-transitory computer-readable storage medium forupdating map data provided for autonomous driving.

BACKGROUND

A conceivable technique provides for storing position information suchas landmarks using an image captured by a camera mounted on the vehicle,uploading the information to a server or the like to generate a roughmap, and determining the position of the own vehicle by downloading thegenerated rough map.

SUMMARY

According to an example, a method for generating or updating map dataincluding coordinate information of a plurality of landmarks disposedalong a road, includes: by a vehicle-side device, uploading indexinformation, indicating that the map data needs to be updated to theserver in associated with a road segment in which the vehicle istraveling when a predetermined event occurs in a situation where thevehicle is traveling; by the server, determining whether the map datafor the road segment needs to be updated based on the index informationprovided by the vehicle-side device; and by a server, setting an updateflag indicating that the map data needs to be updated for the roadsegment when determining that the map data needs to be updated.

BRIEF DESCRIPTION OF THE DRAWINGS

The above and other objects, features and advantages of the presentdisclosure will become more apparent from the following detaileddescription made with reference to the accompanying drawings. In thedrawings:

FIG. 1 is a block diagram showing a schematic configuration of a mapsystem;

FIG. 2 is a diagram showing an example of information included in mapdata;

FIG. 3 is a conceptual diagram showing an example of the feature of mapdata;

FIG. 4 is a flowchart showing upload control of probe data by the mainprocessor;

FIG. 5 is a diagram showing a low frequency area (or a prohibited area);

FIG. 6 is a flowchart showing an example of control executed by a serverprocessor;

FIG. 7 is a diagram showing the dispersion of landmarks;

FIG. 8 is a diagram showing a relationship between a reference mark andother landmarks;

FIG. 9 is a flowchart showing a correction process using a referencemark;

FIG. 10 is a flowchart showing an example of control executed by aserver processor;

FIG. 11 is a flowchart showing an example of control executed by a mainprocessor;

FIG. 12 is a flowchart showing an example of control executed by a mainprocessor;

FIG. 13 is a flowchart showing an example of control executed by a mainprocessor;

FIG. 14 is a flowchart showing an example of control executed by a mainprocessor;

FIG. 15 is a diagram showing a blind spot when the distance between theown vehicle and the preceding vehicle is short.

FIG. 16 is a diagram showing a blind spot when the distance between theown vehicle and the preceding vehicle is relatively long.

FIG. 17 is a flowchart showing an example of control executed by a mainprocessor;

FIG. 18 is a diagram showing a light distribution state in antiglarelight distribution;

FIG. 19 is a flowchart showing an example of control when a destinationis not set;

FIG. 20 is a diagram showing an example of a map tile as a downloadtarget;

FIG. 21 is a flowchart showing control when a destination is set;

FIG. 22 is a diagram showing an example of a map tile as a downloadtarget;

FIG. 23 is a block diagram showing a modified example of theconfiguration of the in-vehicle system; and

FIG. 24 is a block diagram showing a modified example of theconfiguration of the in-vehicle system.

DETAILED DESCRIPTION

The accuracy of the map is important in a system such as the map systemaccording to the conceivable technique, which downloads map informationstored in a server and performs various controls such as automaticsteering of a vehicle based on the information.

The actual location of landmarks may change during the day due tonatural disasters such as earthquakes and heavy rains. In addition tonatural disasters, human factors such as the creation of new residentialareas and urban development may also cause rapid changes. Therefore, themap information needs to be updated from time to time.

Therefore, a map system, a vehicle-side device, a method, and anon-transitory computer-readable storage medium are provided for causinga computer to execute them, which can clearly distinguish the necessityof updating the map information.

An example of a map system is a map system for generating or updatingmap data including coordinate information of a plurality of landmarksexisting along a road, and includes a vehicle-side device used in avehicle, and a server that manages map data. The vehicle-side deviceincludes at least one processor, and the processor is configured toupload the index information, indicating that the map data needs to beupdated, to the server in association with the road segment on which thevehicle is traveling when a predetermined event occurs in a situation oftraveling using the map data. The server determines whether or not themap data for the road segment needs to be updated, based on the indexinformation provided by the vehicle-side device. When determining thatthe update is necessary, the server sets an update flag indicating thatthe map data needs to be updated for the road segment.

In the map system, the update flag indicating that the map informationneeds to be updated is set based on a predetermined condition determinedin advance, so that it is possible to clearly distinguish whether or notthe map information needs to be updated. Further, the examples of thevehicle-side device, the method, and the storage medium disclosed inthis specification correspond to the above-mentioned map system.

The following will describe embodiments for carrying out the presentdisclosure with reference to the drawings. In each embodiment, portionscorresponding to the elements described in the preceding embodiments aredenoted by the same reference numerals, and redundant explanation may beomitted. When only a part of a configuration is described in anembodiment, another preceding embodiment may be applied to the otherparts of the configuration. It may be possible not only to combineparts, the combination of which is explicitly described in anembodiment, but also to combine parts of respective embodiments, thecombination of which is not explicitly described, if any obstacle doesnot especially occur in combining the parts of the respectiveembodiments.

(General Configuration)

First, with reference to FIG. 1, the schematic configuration of the mapsystem 1 to which the present disclosure is applied will be described.

As shown in FIG. 1, the map system 1 includes at least one vehicleequipped with an in-vehicle system 2 described later, and a server 3 inwhich map information (hereinafter, also referred to as map data) isstored. Although FIG. 1 shows only one block representing a vehicle onwhich the in-vehicle system 2 is mounted, the map system 1 may include aplurality of system-mounted vehicles. Each vehicle is configured to becapable of wireless communication with the server 3. The vehicle cantravel on the road and travels while sequentially collecting probe dataas described later. Further, the vehicle is equipped with an automaticdriving system or a driving support system, and performs driving controlusing map data acquired from the server 3.

The vehicle to which the in-vehicle system 2 is applied may be apassenger car, a transportation vehicle such as a truck, or a servicevehicle such as a taxi. Service vehicles also include shared buses (inother words, fixed-route buses), long-distance buses, and vehicles usedfor sharing services such as car sharing and ride sharing. The sharedbus may be an autonomous driving bus that automatically travels on apredetermined route.

The map system 1 corresponds to a system for autonomously driving avehicle along a road segment by using map data including coordinateinformation of a plurality of features existing along the road accordingto one aspect. The expression “along the road” includes not only theside of the road but also the upper part of the road and the surface ofthe road. For example, a direction signboard or a beacon station located3 meters or more above the road surface also corresponds to a featurearranged along the road. In addition, road markings such as lanemarkings made of paint or road studs also correspond to featuresexisting along the road. The term “along the road” can be rephrased ason the road and around the road. The above features also include theroadside itself. The level of automatic driving using map data is notlimited to level 3 or higher, and may correspond to level 2. In theautomation level 2 here, a system including an ECU executes a subtask ofvehicle motion control in both the vertical direction and the horizontaldirection in a limited area, for example, steering correction formaintaining a lane and speed adjustment are automatically performed.Automation level 3 here is that the system performs all drivingoperations within a specific location (ODD: Operational Design Domain),while switching authority to the occupant in the driver's seat occupantswhen it is difficult to continue operation. Automation level 4 is alevel at which the duty of monitoring by the driver's seat occupantspecified in level 3 is removed. Automation level 5 refers to a level atwhich fully autonomous driving is possible on all roads.

The in-vehicle system 2 mounted on each vehicle includes a camera 10 asan imaging device, an image processor 20, a sensor 30 as a stateacquisition unit for acquiring the state of the vehicle, a mainprocessor 40, a communication module 50, and a human machine interface60 (hereinafter, HMI), an actuator 70, and a memory 80. The in-vehiclesystem 2 corresponds to a vehicle-side device or a vehicle controldevice. Hereinafter, regarding the main processor 40, the vehicle onwhich the main processor 40 is mounted is also referred to as a subjectvehicle.

The map system 1 functions additionally to the function of specifyingthe position of the subject vehicle such as GPS, and is effective inspecifying the position of the subject vehicle with higher accuracy. Themap system 1 has roughly two functions, i.e., a map utilization functionand a map update function. In map utilization function, the mapinformation stored in the server 3 is downloaded to the vehicle, and thevehicle itself specifies the position of the subject vehicle based onthe downloaded map information and the position of a landmark such as atraffic sign included in the image captured by the camera 10. On theother hand, in the map update procedure, the information obtained by thecamera 10 and the sensor 30 mounted on the vehicle is uploaded to theserver 3 as probe data, and the map information in the server 3 issequentially updated. As a result, the position of the vehicle is alwaysspecified with high accuracy based on the latest map information, andfor example, driving assistance and automatic steering operation arerealized. After that, the process for determining the detailed positionof the subject vehicle on the road on which the subject vehicle istraveling based on the map data acquired from the server 3 and thecoordinates of the landmark 63 calculated from the image generated bythe camera 10 is defined as a localization process.

The camera 10 is mounted on the vehicle and shoots an image of theenvironment around the vehicle at a wavelength in the visible lightregion. The camera 10 captures, for example, the environment in front ofthe vehicle. Of course, as another aspect, the camera 10 may not belimited to capture the front of the vehicle, and may be configured tocapture at least one of the rear and the side of the vehicle. Further,the vehicle may be provided with a plurality of cameras 10. For example,the vehicle may include four cameras 10, i.e., a front camera thatcaptures a predetermined front range, a rear camera that captures apredetermined rear range, a right camera that captures the right side,and a left camera that captures the left side. In addition, the frontcamera may include a distant camera for capturing a relatively longdistance image and a short-range camera for capturing a short distanceimage. The camera 10 may be a wide-angle camera having an angle of viewexceeding 100 degrees. In addition, the wavelength of light captured bythe camera 10 may not be limited to visible light, and may includeultraviolet and infrared light. For example, the camera 10 may be aninfrared camera. In addition, the vehicle may be equipped with a visiblelight camera that capture visible light and an infrared camera. Thecamera 10 is configured as a camera module including, for example, aCMOS image sensor which is an image sensor (not shown) and an imageprocessing engine (not shown). The information on the environment aroundthe vehicle captured by the camera 10 is stored in the memory 80 in theform of a still image or a moving image (hereinafter, these arecollectively referred to as an image). The image processor 20, whichwill be described later, executes various processes based on the datastored in the memory 80. In a configuration in which the vehicleincludes a plurality of cameras 10, an image processor 20 may beprovided for each camera 10, or one image processor 20 may be configuredto process image data taken by the plurality of cameras 10. Theconfiguration and arrangement of functions related to the camera 10 maybe changed as appropriate.

The image processor 20 analyzes the image captured by the camera 10. Theimage processor 20 detects a predetermined feature, for example, byanalyzing an image. The feature as a detection target is, for example, astructure required for vehicle control. Further, the feature to bedetected corresponds to an element to be recorded in the map data(hereinafter, also referred to as a map element) from another viewpoint.Features detected by the image processor 20 include, for example, roadmarkings (or traffic markings) and landmarks.

Road markings mainly refer to a paint drawn on the road surface fortraffic control and traffic regulation. Road markings include regulatorymarkings and instruction markings. For example, road markings includelane boundaries (so-called line markings, or lane marks) that indicatesa boundary of lanes, pedestrian crossings, stop lines, diversion zones,safety zones, regulatory arrows, and the like Road markings also includethose realized by road studs such as chatter bars and bot dots.

The landmark 63 includes, for example, a traffic regulation sign, asignboard corresponding to a traffic sign such as a guide sign, awarning sign, an instruction sign, a traffic light, a pole, a guideboard, and the like. The guide signboard refers to a directionsignboard, a signboard indicating an area name, a signboard indicating aroad name, a notice signboard indicating an entrance/exit of anexpressway, a service area, etc. The landmark 63 may include streetlights, mirrors, utility poles, commercial advertisements, stores,iconic buildings such as historic buildings, and the like. The pole alsoincludes street lights and utility poles. In addition, a part of theroad marking (for example, a lane mark or a stop line) can be treated asa landmark. The landmarks also include road pavement, undulations,joints, etc. When extracting a landmark, the image processor 20separates and extracts the background and the landmark 63 from thecaptured image based on the image information including the color, thebrightness, the contrast related to the color and the brightness, andthe like. Further, the landmark 63 may be extracted based on the size,shape, and installation position.

Further, the image processor 20 uses the SfM (Structure from Motion)technology to obtain the state quantity showing the behavior(hereinafter, behavior information) of the vehicle such as the yaw rateacting on the own vehicle, the front-rear direction acceleration, thelateral acceleration, the wiper operating state, and the like from thecaptured image of the camera 10. The camera 10 corresponds to an exampleof a peripheral monitoring sensor.

The in-vehicle system 2 of the present embodiment includes a camera 10as a peripheral monitoring sensor, but the peripheral monitoring sensorconstituting the map system 1 may not be limited to the camera 10. Theperipheral monitoring sensor may be a millimeter wave radar or LiDAR(Light Detection and Ranging/Laser Imaging Detection and Ranging). TheLiDAR may be a scanning type LiDAR or a flash type LiDAR. The LiDAR maybe preferably SPAD LiDAR (Single Photon Avalanche Diode Light DetectionAnd Ranging) from the viewpoint of resolution and the like. In addition,various object detection devices such as sonar may be used as peripheralmonitoring sensors. The three dimensional ranging point group datagenerated by the LiDAR, the detection result of the millimeter waveradar, the detection result of the sonar, and the like correspond to theperipheral object data. The three-dimensional ranging point group datais also defined as a distance image. When the three-dimensional rangingpoint group data is used as peripheral object data, the detection objectmay be recognized by using the distance information and the receptionintensity information of each ranging point and each direction. Variousmethods may be used as object recognition methods using LiDAR,millimeter-wave radar, sonar, and the like. In addition, the map system1 may include a plurality of types of devices as peripheral monitoringsensors. For example, the map system 1 may include, as a peripheralmonitoring sensor, a LiDAR configured to cover the front of the vehiclein the detection range in addition to the front camera, which is thecamera 10. A technique (so-called sensor fusion technique) in which thedetection results of a plurality of types of sensors are used togethermay be used for recognizing an object corresponding to a landmark. Whenthe front camera and the millimeter wave radar are used in combination,the accuracy of detecting the distance to the landmark can be improved.In addition, even in an environment where the landmark recognitionaccuracy by the front camera deteriorates, such as at night, thelandmark recognition rate can be ensured by using the detection resultsof the millimeter wave radar in a complementary manner. A camera 10 thatcaptures the front scenery of the vehicle, a millimeter-wave radar, aLiDAR, and the like correspond to a front monitoring device.

The sensor 30 which is a state acquisition unit includes, for example, aspeed sensor, an acceleration sensor, a yaw rate sensor (in a broadsense, a gyro sensor), a steering angle sensor, an illuminance sensor,and a positioning sensor (for example, a GPS receiver) 30 a. Each of theabove sensors acquires, for example, the following vehicle states. Theacquired information indicating the state of the vehicle is stored inthe memory 80.

The speed sensor acquires the speed of the vehicle. The accelerationsensor acquires the acceleration in the traveling direction of thevehicle and the acceleration in the direction orthogonal to thetraveling direction. The yaw rate sensor acquires the yaw rate acting onthe vehicle. The steering angle sensor acquires the steering angle ofthe steering. The illuminance sensor acquires the brightness around thevehicle. The GPS receiver as the positioning sensor 30 a sequentiallyacquires and outputs coordinate information (latitude, longitude,altitude) indicating the current position of the vehicle. The GPSreceiver is configured to output data such as the GPS Doppler speed, thenumber and elevation angles of the acquired positioning satellites, thepseudo distance, the SN ratio of the received satellite signal, andexistence or non-existence of the usage of the correction information.Information such as the elevation angle, the SN ratio, and the usagestatus of the correction information correspond to an index showing theaccuracy of the positioning result. Although the aspect of using GPS asa GNSS (Global Navigation Satellite System) is disclosed here as anexample, the GNSS used by the vehicle may be GLONASS, BeiDou, Galileo,IRNSS, or the like.

Further, for example, the pavement state and undulations of the road onwhich the vehicle is traveling, joints between the bridge and otherroads, and the like can be detected by a sensor or the like that detectsthe vibration of the vehicle. These road pavement states, undulations,joints, and the like can also be adopted as landmarks 63 for specifyingthe position on the map.

The main processor 40 is communicably connected to the image processor20 and the sensor 30 described above, and calculates and processesvarious information input from the image processor 20 and the sensor 30.The main processor 40 generates, for example, a travelling trajectory onwhich the vehicle is predicted to travel based on the speed,acceleration, and yaw rate of the vehicle. That is, the main processor40 generates a travel plan (so-called pass plan) for autonomous driving.The pass plan includes not only setting of the traveling trajectory, butalso determining of the steering control amount at each time point, thetarget vehicle speed, and the timing of transferring the drivingauthority to the occupants. As the yaw rate, the acceleration in thefront-rear direction, and the acceleration in the lateral direction,values detected by the image processor 20 from the image captured by thecamera 10 using the SfM technique may be used. For example, the mainprocessor 40 may be configured to use the output value of the yaw ratesensor as the sensor 30 when the image processor 20 cannot detect theyaw rate. Generally, the yaw rate determined from the image captured bythe camera may be more accurate than the yaw rate detected by the yawrate sensor. Therefore, the main processor 40 can improve the accuracyof dead reckoning, for example, by using the value detected by the imageprocessor 20 as the yaw rate. Here, the yaw rate based on the imageanalysis and the yaw rate derived from the sensor 30 may be used in acomplementary combination manner. Further, the main processor 40generates a traveling history indicating the actually traveled trackbased on the history of the own vehicle position specified by deadreckoning or localization described later.

Further, the main processor 40 generates a trajectory (specifically,shape data such as curvature and width) on the travelling road based onthe lane mark detected based on the image acquired by the camera 10.Further, the main processor 40 calculates the position coordinates(hereinafter, also referred to as observation coordinates) in the globalcoordinate system of features such as landmarks 63 and lane marksextracted by the image processor 20.

The position coordinates of the feature may be specified by combiningthe current position of the own vehicle and the relative positioninformation of the feature with respect to the own vehicle. The relativeposition (i.e., distance and direction) of the feature with respect tothe own vehicle may be specified based on the size and posture (forexample, the degree of inclination) of the feature in the image. Themain processor 40 roughly estimates the initial coordinates of thevehicle in the global coordinate system by, for example, GPS. Then, therelative coordinates from the initial coordinates of the vehiclecalculated by integrating the speed vector of the vehicle are estimated.This gives a rough current position of the vehicle in the globalcoordinate system. Further, the relative distance and direction offeatures such as landmarks and lane marks from the vehicle arecalculated from an image including SfM (Structure from Motion)information. As a result, the global coordinates of the position wherethe feature such as a landmark exists can be obtained. The relativedistance and direction of the landmark from the vehicle may becalculated using information from a millimeter-wave radar or laser radar(not shown). The coordinate calculation of the feature may be executedby the image processor 20.

Feature information and track information as a result of calculation,processing, or acquisition by the main processor 40 are temporarilystored in the memory 80. The feature information is informationindicating the position coordinates, shape, and size of the featurespecified by image recognition. In the memory 80, each object isrepresented by, for example, a group of coordinate points arranged alongthe contour of the feature. Various modes can be adopted as theexpression form of the shape and position of the feature. For example,the shape and position of the feature may be represented by apolynomial.

The feature information can be roughly divided into landmark informationand lane mark information. The landmark information includes the type oflandmark, coordinate information, color, size, shape and the like. Asthe type of landmark, a signboard, a traffic signal, a sign, a pole, apedestrian crossing, a road marking (for example, a stop line), amanhole, and the like can be adopted. The lane mark can also be adoptedas a landmark. The lane mark information includes, for example, positioninformation of the lane mark and information indicating whether the lanemark is realized by a solid line, a broken line, or a bot's dot pattern.The position information of the lane mark is expressed as a coordinategroup (that is, a point cloud) of the points where the lane mark isformed. As another aspect, the position information of the lane mark maybe represented by a polynomial. The position information of the lanemark may be a set of line segments (that is, a group of lines)represented by a polynomial.

In addition, the main processor 40 executes various processes related tomap utilization and map update (or generation). As a process related tomap update, the main processor 40 executes, for example, downloading mapinformation, uploading probe data, selecting landmarks used forlocalization, and the like. Some specific examples of various processesrelated to map utilization and map update (or map generation) will bedescribed in detail later.

The communication module 50 is interposed between the main processor 40and the server 3 so that the main processor 40 and the server 3described later can communicate with each other. The communicationmodule 50 transmits the probe data input from the main processor 40 tothe server 3. Further, the communication module 50 receives the mapinformation and related information stored in the server 3 and storesthem in the memory 80. The main processor 40 is configured to executevarious controls such as steering control, acceleration, and braking ofthe vehicle based on the map information received via the communicationmodule 50 and stored in the memory 80.

The HMI 60 is a user interface for notifying the user of variousinformation and for the user to transmit a predetermined operation tothe vehicle. As the HMI 60, for example, a display attached to a carnavigation device, a display built in an instrument panel, a head-updisplay projected on a windshield, a microphone, a speaker, and the likecan be adopted. Furthermore, a mobile terminal such as a smartphone thatis communicably connected to the vehicle can also be an HMI 60 in themap system 1.

In addition to visually obtaining the information displayed on the HMI60, the user can also obtain the information by voice, warning sound, orvibration. In addition, the user can request the vehicle device toperform a desired operation by touch operation of the display or voiceoperation.

For example, when the user intends to receive a service of advanceddriving support such as automatic steering by utilizing the mapinformation, the user activates the function via the HMI 60. Forexample, tapping the “Map Link” button shown on the display activatesthe map utilization function and starts downloading map information. Inanother example, the map utilization function is enabled by inputting avoice command. The map information related to the map update may beuploaded at all times while the communication between the vehicle andthe server 3 is established, or while the map utilization function iseffective by tapping the “Map linkage” button. It may be enabled byanother UI that reflects the user's requests.

The actuator 70 includes, for example, a braking device (so-called brakeactuator), an electronic throttle, a steering actuator, and the like.The actuator 70 is a hardware element relating to at least one ofacceleration, deceleration, and steering of the vehicle.

The memory 80 is realized by using a volatile memory such as RAM. Thememory 80 may be realized by using a non-volatile memory such as a flashmemory. The memory 80 may include both a volatile memory and anon-volatile memory. Here, as an example, the memory 80 includes atemporary storage unit 81 using a volatile memory and a storage unit 82using a non-volatile memory. The storage unit 82 stores a program(hereinafter, a vehicle program) for causing the main processor 40 toexecute processing such as generation of probe data. The vehicle programmay be stored in a non-transitory tangible storage medium.

[Localization]

The main processor 40 identifies (i.e., localizes) the detailed positionof the own vehicle by checking the landmark coordinates calculated basedon the image captured in real time with the landmark coordinatesincluded in the map information downloaded from the server 3.

For example, the main processor 40 performs longitudinal localizationusing landmarks such as direction signs, traffic lights, road signs, andstop lines. The longitudinal direction here corresponds to thefront-rear direction of the vehicle. In addition, the longitudinaldirection corresponds to the direction in which the road extends whenviewed from the own vehicle (hereinafter, also referred to as the roadextension direction) in the straight road section. The localization inthe longitudinal direction corresponds to the process of specifying theposition of the own vehicle in the road extension direction. Forexample, as a result of image analysis, in a situation where thedistance to the direction signboard existing in front of the own vehicleis specified as 100 meters, for example, it is determined that the ownvehicle exists at the position deviated from the position coordinates ofthe direction signboard registered in the map data by 100 meters to theown vehicle side. By performing such longitudinal localization, thedetailed remaining distance to the feature point (in other words, POI)on the road such as intersections, curve entrances/exits, tunnelentrances/exits, and the end of traffic jams can be obtained.

Further, the main processor 40 performs lateral localization usinglandmarks such as lane marks, road edges, and guardrails. Laterallocalization refers to specifying of the driving lane and specifying ofthe detailed position of the own vehicle in the driving lane (i.e., theamount of offset from the center of the lane to the left and right). Thelateral direction here refers to the vehicle width direction and theroad width direction. Lateral localization is achieved, for example,based on the distance from the left and right road edges/lane markingsrecognized by the image processor 20. For example, when the distancefrom the left side road edge to the vehicle center is specified as 1.75meters as a result of image analysis, it is determined that the ownvehicle exists at a position shifted by 1.75 meters to the right fromthe coordinates of the left side road end. The vehicle position as aresult of localization may be represented by a coordinate system (forexample, latitude, longitude, altitude) similar to the map data. Thevehicle position information can be expressed in any absolute coordinatesystem such as WGS84 (World Geodetic System 1984). Further, the vehicleposition information may be represented by a local coordinate systemindicating a position in the map tile described later.

Here, as an example, the type of landmark used for longitudinallocalization and the type of landmark used for lateral localization aredifferent. Here, as another aspect, the main processor 40 may beconfigured to perform longitudinal and lateral localization using onelandmark. When a plurality of landmarks are detected, localization maybe performed using the landmark closest to the own vehicle. For example,when the main processor 40 detects a plurality of landmarks (forexample, direction signs) in front of the own vehicle, the mainprocessor 40 uses the one closest to the own vehicle among the pluralityof landmarks to perform longitudinal localization. As for therecognition accuracy of the type and distance of an object based on animage or the like, the closer the object is to the vehicle, the higherthe recognition accuracy. That is, when a plurality of landmarks aredetected, the position estimation accuracy can be improved by theconfiguration in which the landmark closest to the vehicle is used forlocalization.

The main processor 40 sequentially localizes at predetermined positioncalculation intervals as long as the landmarks can be detected (in otherwords, captured). The position calculation interval is, for example, 100milliseconds. The position calculation interval may be 200 millisecondsor 400 milliseconds. The position calculation interval may bedynamically changed according to the type of road on which the ownvehicle is traveling (hereinafter, the traveling road), the vehiclespeed, and the external environment. For example, when traveling on aroad section where the remaining distance to a curve or intersection iswithin 0.5 km, the interval may be set to a value (for example, 100milliseconds) shorter than a predetermined standard interval (forexample, 200 ms). In the vicinity of curves and intersections, it isnecessary to maintain highly accurate position information of the ownvehicle with respect to those features. In a scene where relativelyadvanced/precise vehicle control (for example, steering control) isperformed such as a curve or an intersection, it is possible to improvethe accuracy of the own vehicle position information by setting theposition calculation interval to be shortly. That is, by providing amode in which the position calculation intervals are made short, it ispossible to more appropriately perform vehicle control based on the ownvehicle position information in a scene where relatively high/precisevehicle control such as on a curve is performed. On the other hand, byproviding a mode in which the position calculation interval is long, theprocessing load of the main processor 40 can be reduced.

The main processor 40 sequentially performs localization when the maputilization function is enabled by the user and detailed map data nearthe current position can be acquired. Whether or not the main processor40 performs localization may be changed according to the type of thetraveling path. For example, when the driving road is a motorway,localization may be performed, but when the driving road is a generalroad, localization may not be performed. The motorway here is a roadwhere pedestrians are prohibited from entering in principle, andincludes toll roads such as expressways, for example. Automobile roadsalso include general roads where traffic other than automobiles isprohibited. The execution/non-execution of localization by the mainprocessor 40 may be determined by the main processor 40 or controlled bythe server 3 based on the state of maintenance of map data, the type oftravel path, and the like.

The main processor 40 performs a dead reckoning process (i.e., DeadReckoning or autonomous navigation) using the yaw rate and the vehiclespeed when localization cannot be performed (for example, when nolandmark is detected) or when the map utilization function is notenabled. The yaw rate used for the dead reckoning may be a yaw raterecognized by the image processor 20 using SfM technology, or may bedetected by a yaw rate sensor.

The main processor 40 outputs a corresponding instruction to theactuator 70 for operating the hardware mounted on the vehicle based onthe current position and map data of the own vehicle specified bylocalization or dead reckoning. As a result, automatic driving anddriving support are realized. The main processor 40 also controlslighting of lamps such as turn signals, hazard lamps, and headlightsaccording to a travel plan generated by the main processor 40 itself oranother ECU (for example, an autonomous driving ECU).

Example of Vehicle Control by Utilizing Maps

By acquiring POI information of a toll gate or the like located acertain distance (for example, 200 meters) ahead of the current positionfrom the map data, the main processor 40 can control the vehicle such aslane change and deceleration with a sufficient margin (in other words,more safely). The POI here refers to a point that should be noted fromthe viewpoint of vehicle control and pass plan. For example, the POIincludes map elements that affect vehicle travel control, such as curveentrances/exits, tunnel entrances/exits, and the beginning and end oftraffic jams. The POI includes a static POI corresponding to static mapinformation and a dynamic POI corresponding to dynamic map information.Dynamic POI refers to the end position or the top position of a trafficjam.

Here, as an example, the usefulness of map utilization will be describedby taking the case of automatically driving a vehicle using map data asan example. In addition, there is ACC as an application (hereinafter,also referred to as an application) related to automatic control of avehicle. ACC stands for Adaptive Cruise Control.

It refers to a function of automatically driving a vehicle so that thedistance between the vehicle and the preceding vehicle is constantwithin a range in which the traveling speed of the vehicle does notexceed a predetermined upper limit value. In addition, the applicationrelated to automatic vehicle control (hereinafter, also referred to asthe vehicle control application) includes an application that drives thevehicle so as to maintain the center of the lane (hereinafter referredto as the lane keeping application), or a function for supporting orautomatically executing operations related to lane change (hereinafter,lane change application).

For example, in the lane keeping application, it is necessary to detectthe lane shape (such as curvature, and the like) in front of the vehiclein advance and adjust the steering operation amount. However, when thefront of the vehicle is a blind corner or the field of view isobstructed by the preceding vehicle in front, the camera 10 may not beable to recognize the shape of the lane in front. In addition, it may bedifficult for the camera 10 to recognize the shape of the lane in frontdue to weather conditions such as rain or snow that impairs thevisibility ahead. In such cases, by acquiring the curvature of the roadahead using map data and complementing the recognition result of thecamera 10, the risk of the lane keeping application being interruptedcan be reduced (in other words, the application can continue to beexecuted).

Further, in ACC, it is necessary to detect the curvature of the roadahead of the vehicle in advance and adjust the speed. For example,control to decelerate to a predetermined target speed may be executedbefore the curve so that the vehicle can travel smoothly and safely onthe curve. However, as described above, it may be difficult for thecamera 10 to recognize the front lane shape depending on the precedingvehicle, weather conditions, and road shape. In response to such adifficulty, according to the configuration in which the curvature of theroad ahead is acquired in advance using map data, even if the curvatureof the road ahead cannot be detected by the camera 10, by the time thevehicle enters the curved section, it is possible to automaticallydecelerate to the target speed according to the curvature of the forwardcurve.

Further, when the ACC function is turned on, the vehicle may betraveling at a speed lower than a predetermined target speed accordingto the speed of the preceding vehicle. Under such circumstances, whenthe preceding vehicle moves due to a lane change or the like (in otherwords, when the preceding vehicle leaves the front of the own vehicle),the ACC function usually accelerates the vehicle to a predeterminedtarget speed. However, there are some sections, such as before the tollgate and the exit route of the expressway, where acceleration due to thedisappearance of the preceding vehicle may not be proper. In response tosuch a situation, according to the map utilization function, it ispossible to determine whether the current position is disposed in a roadsection in which acceleration is preferable based on the map data. Whenthe current position is in front of the toll gate (for example, within200 meters), the acceleration to the target speed can be canceled. Thatis, by utilizing the map data, the risk of performing unnecessaryacceleration can be reduced. The section where acceleration to the ACCset speed is not preferable refers to the vicinity of a toll gate, theexit route of an expressway, the vicinity of an intersection, a sharpcurve, or the like.

Although various examples have been disclosed above, vehicle control byutilizing a map is not limited to the above. The map data is also usefulwhen the driver's seat occupant (so-called a driver) has the drivingauthority. The POI information such as traffic jams that are disposed ata certain distance away from the current position may be notified to thedriver as support information for driving operations.

[Generation of Probe Data by the Main Processor]

The main processor 40 transmits a data set including the traveltrajectory information, the travelling route information, and thefeature information stored in the memory 80 to the server 3 as probedata. The traveling trajectory information is information indicating thetrajectory on which the own vehicle has traveled. For example, thetraveling trajectory information is expressed as a sequence of points ofthe own vehicle position. The travelling route information isinformation indicating the travelling route of the end and the centerline of the travelling path. The end of the traveling path and the likemay also be represented by a group of coordinate points. The travellingroute information directly or indirectly indicates the road shape suchas the curvature and width of the road.

Specifically, the main processor 40 sequentially acquires featureinformation, travelling route information, and own vehicle positioncoordinates (hereinafter, recognition results) obtained by imagerecognition or the like, and stores the information in the memory 80 inchronological order so as to connect to the acquisition time (in otherwords, observation time). The recognition result of the featureinformation or the like is sequentially provided by, for example, theimage processor 20 (for example, every 100 milliseconds). The featureinformation may be sequentially generated by the main processor 40 incollaboration with the image processor 20.

The recognition result data at each time stored in the memory 80 arecollectively uploaded at predetermined upload intervals. The uploadinterval is set to, for example, K (K is a natural number) times theexecution cycle of the image recognition process. When an equation of K2 is satisfied, the main processor 40 uploads the data in which therecognition result within a certain period of time stored in the memory80 is packaged as probe data. Here, as an example, K=4 is set. That is,the main processor 40 uploads the data in which the recognition resultwithin 400 milliseconds is packaged as probe data. The data includingthe vehicle positions at a plurality of time points corresponds to theabove-mentioned traveling trajectory information.

The probe data sequentially transmitted by the vehicle is stored in theserver 3 in a predetermined storage/management format. For example, theserver 3 stores probe data sequentially transmitted by the same vehicleto combine in a length including a predetermined number of landmarks.The length of the probe data may correspond to a unit of road segments.A road segment is a road management unit in map data. A road segment isa division of roads according to predetermined rules. The road segmentmay correspond to, for example, a road link. The road link here refersto a road section connecting road nodes indicating intersections and endpoints of roads. Alternatively, the road segment may be a furthersubdivision of the road link. The road segment may be a road segmentedby a predetermined length (for example, every 10 meters).

Here, as an example, it is defined that each vehicle (actually, thein-vehicle system 2) uploads data expressing the vehicle's travelingtrajectory and road edge and the like in a coordinate point sequence,alternatively, as another aspect, the traveling trajectory and roadedges, lane center lines, and the like may be represented bypolynomials. Further, instead of the vehicle position information, themain processor 40 may upload the positioning result by GPS, the SfMinformation, and the vehicle speed information, and the server 3 may beconfigured to calculate the vehicle position at each time point based onthe information. The feature information and the travelling trajectoryinformation included in the probe data correspond to the information forthe server 3 to generate the static map (hereinafter, staticinformation) in one aspect.

In addition, the probe data may include dynamic information indicatingthe behavior of the vehicle (hereinafter referred to as vehicle behaviorinformation) such as the vehicle speed within the latest predeterminedtime interval, steering angle, yaw rate, blinker operation information,lane ID, and relative position with respect to the lane. The vehiclebehavior information includes wiper operation information, shiftposition, vehicle body orientation, vehicle body pitch angle, rollangle, inter-vehicle distance from the preceding vehicle, and the like.The relative position information with respect to the lane refers to theamount of offset to the left and right with respect to the lane centerline, whether the vehicle body straddles the lane, and the like.

By acquiring vehicle behavior information, the server 3 acquires POIinformation corresponding to quasi-dynamic map information, such as acongested section or a point where there is an obstacle such as afalling object or a parked vehicle on the street. For example, theserver 3 adopts the end of the vehicle group whose vehicle speed isequal to or less than a predetermined threshold value as the tail end ofthe traffic jam section, and sets the point corresponding to the tailend as the dynamic POI related to the traffic jam. Further, the headposition of the vehicle group whose vehicle speed is equal to or lessthan a predetermined threshold value is adopted as the head position ofthe traffic jam section, and the head position is set to the dynamicPOI. Further, the server 3 defines a point where a certain number ofvehicles (for example, 10 vehicles) or more are temporarily travelingacross lanes or changing lanes, as a place where there are obstaclessuch as falling objects and vehicles parked on the street (hereafter, itis regarded as an obstacle existence point). Then, the obstacleexistence point is set to the dynamic POI.

The map data stored in the server 3 includes a road segment 62 in whichthe shape of the road is represented by a cubic spline curve and alandmark 63 existing around the road segment 62, as shown in FIG. 2, forexample. Road segment 62 and landmark 63 have latitude, longitude andaltitude values, respectively. The landmark 63 includes, for example, atraffic sign, and information obtained in real time by the camera 10 andvarious sensors 30 as a state acquisition unit, as well as informationwhose position has already been determined, is integrally configured onthe map. Map information is updated sequentially based on theinformation obtained in real time.

FIG. 3 conceptually shows an example of the structure of map data. Asshown in FIG. 3, the map data includes road network data, lane networkdata, feature data, and POI data. Each data is hierarchically organized.The road network data includes link ID, link length, number of lanes,and connection node information (for example, node ID) for each roadlink, and node ID, position coordinates, and connection link information(for example, link ID) for each road node. The lane network dataincludes lane ID, link ID at lane level, link length, and connectionnode information, and node ID, position coordinates, and connection linkinformation (for example, link ID) for each lane node. The linkinformation at the lane level included in the lane network data isassociated with the road link included in the road network data.

The feature data includes lane marking data and landmark data. The lanemarking data includes a lane marking ID for each lane marking and agroup of coordinate points representing an installation portion. Thelane marking data includes pattern information such as broken lines,solid lines, and road tacks. The lane marking data is associated withlane information (e.g., lane ID or link ID at the lane level). Thelandmark data represents the position and type of each landmark. Theshape and position of each object are represented by a group ofcoordinate points. POI data is data indicative of the position and thetype of the feature which affects vehicle travel plans such as branchpoints for exiting the main highway, junctions, speed limit changepoints, lane change points, traffic jams, construction sections,intersections, tunnels, toll gates, etc. POI data includes type andlocation information.

In addition, the map data may include a traveling trajectory model. Thetravel trajectory model is track data generated by statisticallyintegrating the travel trajectories of a plurality of vehicles. Thetravel trajectory model is, for example, an average of travelingtrajectories for each lane. The traveling trajectory model correspondsto data indicating a traveling track that serves as a reference duringautomatic driving.

The map data may include static map information and dynamic mapinformation. The static map information here is information aboutfeatures that are unlikely to change, such as road networks, roadshapes, road markings, structures such as X guardrails, and buildings(for example, information about features that need to be updated withinone week to one month). Static map information is also called a basemap. Dynamic map information refers to information about map elementswhose state changes in a relatively short period of time, such as roadconstruction information and traffic regulation information. The dynamicmap information may be classified into quasi-static information,quasi-dynamic information, and dynamic information (hereinafter, hyperdynamic information) that changes in seconds according to the expectedvalue of the duration of the state (in other words, the speed ofchange). Quasi-static information is, for example, information that isrequired to be updated within one to several hours. Road constructioninformation, traffic regulation information, traffic congestioninformation, and wide area weather information correspond to thequasi-static information. Semi-dynamic information is, for example,information that is required to be updated every 10 minutes. The tailend position of traffic jam, accident information, narrow area weatherinformation, falling objects on the road, and the like correspond to thesemi-dynamic information. The hyper dynamic information includes, forexample, position information of a moving body such as a vehicle or apedestrian, and ITS (Intelligent Transport Systems) information such asa lighting state of a traffic light.

Here, as an example, the map data handled by the map system 1 mayinclude static map information, quasi-static map information, andquasi-dynamic information. Alternatively, the map information handled bythe map system 1 may only include static map information. It may alsoinclude hyperdynamic information. The static map information and thedynamic map information may be configured to be managed (i.e., updatedand distributed) separately.

The server 3 stores the map information and updates the map informationby the server processor 31 attached to the server 3. All map datacorresponding to all map recording areas are divided into a plurality ofpatches and managed. Each patch corresponds to map data for differentareas. In addition, each patch may partially overlap at thecorresponding region with the adjacent patch.

For example, the map data is stored in units of map tiles in which themap recording area is divided into 2 km square rectangles. Hereinafter,for convenience, the real space range (i.e., a rectangular divided area)to be recorded by the map tile is also simply referred to as the maptile. A plurality of map tiles are stored in the server 3 together withthe corresponding latitude, longitude, and altitude information. Eachmap tile is given a unique ID (hereinafter, tile ID). Map tilescorrespond to the subordinate concept of the patch described above.

The size of the map tile can be changed as appropriate, and is notlimited to a 2 km square rectangle. It may have a rectangular shape of 1km square or 4 km square. Further, the map tile may be hexagonal orcircular. Each map tile may be set to partially overlap adjacent maptiles. The size of the map tiles may vary from layer to layer. Forexample, the tile size of static map data may be set to 2 km square,while the tile size of dynamic map data (particularly map data relatedto quasi-dynamic information) may be set to 1 km square. The tile sizemay differ depending on the type of road, such as an expressway and ageneral road. The tile size of a general road may be preferably setsmaller than the tile size of an expressway. In addition, general roadsmay also be distinguished by trunk roads and narrow streets. In thatcase, it may be preferable that the tile size of the narrow street isset smaller than that of the trunk road. The map recording area may bethe entire country where the vehicle is used, or may be only a part ofthe area. For example, the map recording area may be limited to an areawhere automatic driving of a general vehicle is permitted or an areawhere an automatic driving operation service is provided.

Further, here, as an example, the server 3 manages (i.e., generates,updates, and distributes) map data in units of map tiles in which themap recording area is divided into rectangular shapes of uniform size,alternatively, it is not limited to this. The size and shape of the maptiles may be non-uniform. That is, the size and shape of thepatch-corresponding area, which is the range of the real worldcorresponding to each patch (in other words, the range as a registrationtarget), may be uniform or various. For example, a map tile in a ruralarea where the density of map elements such as landmarks is likely to berelatively sparse may be larger than a map tile in an urban area wheremap elements such as landmarks are likely to be densely present. Forexample, the map tiles in the rural area may have a rectangular shape of4 km square, while the map tiles in the urban area may have arectangular shape of 1 km square or 0.5 km square. The urban area hererefers to, for example, an area where the population density is equal toor larger than a predetermined value or an area where offices andcommercial facilities are concentrated. Rural areas may be areas otherthan urban areas. Rural areas may be defined as countryside areas. Theclassification mode of the area may not be limited to the two stages ofurban area and rural area. The map recording area may be divided intofour stages in descending order of population density: urban area, ruralarea, countryside area, and depopulated area. In addition to populationdensity, the number of companies, the usage of the area designated bythe government, and the land usage rate may be adopted as the criteriafor dividing the area. The degree of urbanity in a region may bedetermined by combining multiple types of indicators.

In addition, the division mode of all map data may be defined by thedata size. In other words, the map recording area may be divided andmanaged within a range defined by the data size. In that case, eachpatch is set so that the amount of data is less than a predeterminedvalue. According to such an aspect, the data size in one delivery can beset to a certain value or less. The real space range supported by thepatch in the urban area may be narrower than the real space rangesupported by the sub blocks in the rural area. As mentioned above, it isexpected that map elements such as landmarks and lane marks will be moredensely present in urban areas than in rural areas.

While the map coordination (in other words, map utilization) function isturned on, the vehicle travels based on the downloaded map data whilesequentially obtaining the information of the map tile to which thepassing road belongs from the server 3. Regarding the handling of themap data downloaded to the in-vehicle system 2, various rules can beapplied in consideration of the capacity of the memory 80 and the like.For example, when the capacity of the memory 80 is relatively small, themain processor 40 may be configured to delete the map data of the maptile on which the own vehicle has already left, as soon as the vehicleleaves or at a timing when the vehicle is far away by a predetermineddistance or more. According to such a configuration, the in-vehiclesystem 2 can be realized by using the memory 80 having a small capacity.That is, the introduction cost of the in-vehicle system 2 can bereduced.

Further, the map data downloaded to the memory 80 may be configured tobe deleted at a timing when a predetermined time (for example, one day)has elapsed from the time of downloading. Map data of roads used on adaily basis, such as commuting roads and school roads, may be configuredto be cached in the memory 80 as much as possible (for example, unlessthe free space becomes a predetermined value or less). The retentionperiod of the downloaded map data may be changed according to theattributes of the data. For example, static map data is stored in thestorage unit 82 up to a certain amount. On the other hand, for example,dynamic map data such as construction information may not be stored inthe storage unit 82, but be deleted from the temporary storage unit 81when the vehicle passes through the area corresponding to the dynamicmap data.

Here, as an example, all the map data in the memory 80 is deleted atleast when the travelling power source is turned off. The travelingpower source here is a power source for the vehicle to travel, andrefers to an ignition power source when the vehicle is a gasolinevehicle. When the vehicle is an electric vehicle or a hybrid vehicle, itrefers to the system main relay.

[Probe Data Upload Control]

The map system 1 uploads information about the map collected by thevehicle to the server 3 included in the map system 1, and the mapinformation stored in the server 3 can be updated. Uploads are usuallyperformed at a predetermined frequency. For example, the normal uploadinterval is set to 400 milliseconds. Of course, the upload interval maybe 200 milliseconds, 500 milliseconds, 1 second, 2 seconds, or the like.However, under predetermined conditions, the main processor 40 may havean operation mode in which uploading of probe data is stopped, thefrequency thereof is reduced, or the type of information to be uploadedis limited. In the following, a feature in which the main processor 40has a low frequency mode in which the upload frequency is lower than thenormal frequency in addition to the normal mode in which the upload isexecuted at the normal frequency will be described with reference toFIG. 4. FIG. 4 shows an example of a processing flow executed by themain processor 40. The normal mode corresponds to the first mode, andthe low frequency mode corresponds to the second mode.

As shown in FIG. 4, first, step S100 is executed. Step S100 is a step inwhich the main processor 40 determines a rough position of the ownvehicle based on the information of the positioning result by GPS.

Next, step S101 is executed. Step S101 is a step in which the mainprocessor 40 downloads map information corresponding to the roughposition of the own vehicle from the server 3. The determination andacquisition of map information corresponding to the rough position ofthe own vehicle will be described later.

Next, step S102 is executed. Step S102 is a step in which the mainprocessor 40 determines the detailed position of the own vehicle. Thedetailed position of the own vehicle is the global coordinates includinglatitude, longitude and altitude on the earth. The main processor 40determines the detailed global coordinates of the own vehicle based onthe map information downloaded from the server 3 together with the roughposition information using, for example, GPS.

Next, step S103 is executed. Step S103 is a step of determining whetheror not the situation in which the own vehicle is placed satisfies apredetermined low frequency condition. Specifically, it is a step inwhich the main processor 40 determines whether or not the position ofthe own vehicle exists in a predetermined low frequency area determinedin advance. That is, the low frequency condition in the example shown inFIG. 4 is whether or not the position of the own vehicle exists in apredetermined low frequency area determined in advance.

When the situation in which the own vehicle is placed satisfies apredetermined low frequency condition, that is, when the position of theown vehicle exists in a predetermined low frequency area determined inadvance, the determination in step S103 is YES, and the process proceedsto step S104. The low frequency area is predetermined on the map asshown in FIG. 5. The low frequency area may be set as a line along theroad segment 62, or may be set as a plane having a predetermined area asillustrated in FIG. 5.

On the other hand, when the situation in which the own vehicle is placeddoes not satisfy the predetermined low frequency condition, the processproceeds to step S105. Step S105 shows a normal frequency mode in whichthe upload frequency is performed at a normal frequency.

As described above, when the position of the own vehicle exists in apredetermined low frequency area, the process proceeds to step S104, andas shown in FIG. 4, the map system 1 is in the low frequency mode. Theprocess proceeds to step S106 through step S104 or step S105. Step S106is a step of transmitting probe data including map information to theserver 3. The probe data is uploaded to the server 3 at a predeterminedfrequency according to the frequency mode related to the upload of theprobe data set in step S104 or step S105. After that, this flow ends.

The low frequency mode will be described in detail below. When the lowfrequency mode is enabled, the amount of communication data related tothe map information between the communication module 50 and the server 3is reduced as compared with the normal frequency mode. Therefore, theload on the communication line can be reduced, and the cost related tocommunication can be reduced.

A low-frequency area means a region that is disposed in the environmentwhere there are many other vehicles around the own vehicle, for example,a trunk road in an urban area, and a sufficient amount of mapinformation can be uploaded to the server 3 from many other vehicles. Insuch an area, since a large amount of map information is uploaded fromother vehicles, it is possible to secure a sufficient amount ofinformation for updating the map information even if the uploadfrequency of the own vehicle is reduced.

Another example is an area where the frequency of change of landmarks 63such as traffic signs and road markings is relatively low, such as amotorway. In such areas, the update of landmark 63 itself as hardware onand near the road is expected to be infrequent, so even if the uploadfrequency of the own vehicle is reduced, a sufficient amount ofinformation can be secured to update the map information.

In addition, the frequency of uploads can be reduced to zero in lowfrequency mode. The state in which the upload frequency is zero is astate in which uploading of map information to the server 3 issubstantially prohibited, and is particularly referred to as aprohibition mode. That is, the low frequency mode includes theprohibition mode.

The prohibited area, which is a low frequency area where the prohibitionmode is enabled, is a region in a facility that is not suitable forsteering based on automatic steering and has a road that can be drivenby a vehicle such as a safari park, or in a facility having a highlyconfidential building such as a military facility or a private companyfacility. In such a prohibited area, uploading of map information fromthe vehicle to the server 3 is prohibited, and the map is not generatedon the server 3 either. Therefore, the download for vehicle control isnot performed.

Regarding the predetermined condition in which the low frequency mode isenabled, in the above example, whether or not the position of the ownvehicle exists in a predetermined low frequency area is adopted,alternatively, another condition may be adopted.

For example, the normal frequency mode may be changed to the lowfrequency mode at night. At night, it tends to be more difficult for thecamera 10 to recognize traffic signs and road markings than during thedaytime, and the reliability of determining the position of the landmark63 is lower than during the daytime. Therefore, it may be preferable toreduce the frequency of uploading the location information of thelandmark 63 to the server 3. It may be advisable to set in advance atime zone in which the vehicle is placed at night or in a lowilluminance environment equivalent thereto, and set the upload frequencyto the low frequency mode in that time zone. Further, in an area where aseason exists, the time zone defined as nighttime differs depending onthe season, so it may be preferable to make the time zone defined asnighttime variable according to the season. For example, in an area witha midnight sun, the time zone at night is relatively short, and there islittle chance that the surrounding environment of the vehicle hasextremely low illuminance. In such areas, the low frequency mode is alsoenabled for a shorter period of time.

Further, the normal frequency mode may be changed to the low frequencymode based on the weather conditions in the area where the vehicletravels. For example, in bad weather such as heavy rain, heavy snowfall,heavy fog, and sandstorm, it may tend to be difficult to recognizetraffic signs and road markings, and the reliability of determining theposition of landmark 63 may be lower than in fine weather. Therefore, itmay be preferable to reduce the frequency of uploading the locationinformation of the landmark 63 to the server 3. As a method ofdetermining the weather conditions of the vehicle, for example, thereflectance of the road surface is measured using an image captured bythe camera 10, or the weather is determined based on the contrast of theimage. In addition, based on information published by a publicinstitution, areas that meet predetermined weather conditions such asheavy rain, heavy snowfall, heavy fog, and sandstorms may be designatedas low-frequency areas in real time. The setting of the low frequencyarea itself may be dynamically changed according to the weatherconditions, the time zone, and the collection status of probe data (inother words, the degree of accumulation) of the server 3. Areas that arenot infrequent areas (hereinafter referred to as normal areas) may alsobe set as infrequent areas when the probe data is sufficiently collectedin bad weather or at night. The setting change of the area may becarried out by the server 3 or by the vehicle side device.

Further, the upload frequency may be gradually reduced based on theyears of use of the main processor 40 and the image processor 20 (inother words, the total operating time). The performance of the mainprocessor 40 and the image processor 20 is evolving day by day, and itis presumed that the newer the processor, the shorter the time requiredfor image processing and uploading, and the higher the accuracy.Therefore, the longer the processor has been used, the less frequentlythe map information should be uploaded. On the contrary, the mapinformation can be efficiently collected by actively uploading the mapinformation to the processor having been used for a short period oftime.

As described above, the mode of changing the upload frequency of theprobe data based on the traveling area, the weather condition, the timezone, and the number of years of use of the image processor 20 has beendisclosed. Alternatively, the map system 1 may be configured as follows.The main processor 40 includes a full transmission mode and asuppression transmission mode as operation modes. The full transmissionmode corresponds to an operation mode in which a data set includinginformation about all items specified in advance to be transmitted asprobe data is uploaded as probe data. On the other hand, the suppressiontransmission mode is an operation mode in which only a part of all theitems set as upload targets in the full transmission mode is uploaded asprobe data. The full transmission mode corresponds to the first mode inwhich a predetermined type of feature is to be uploaded, and thesuppression transmission mode corresponds to the second mode in whichthe number of features to be uploaded is smaller than the fulltransmission mode as the first mode.

The type of information to be uploaded in the suppression transmissionmode may be set in advance or may be specified by the server 3. The typeof information to be uploaded to the vehicle in the suppressiontransmission mode may be, for example, an item that is insufficient fromthe viewpoint of generating/updating map data. The number of itemsuploaded in the suppression transmission mode may be zero. Thesuppression transmission mode may also include a prohibition mode. Ifthe information to be uploaded in the full transmission mode includesboth static information and dynamic information, the information to beuploaded in the suppression transmission mode may be only dynamicinformation.

In the above configuration, the server processor 31 instructs thevehicle existing in the predetermined upload suppression section tooperate in the suppression transmission mode. Further, the serverprocessor 31 instructs the vehicle existing in the section other thanthe upload suppression section to operate in the full transmission mode.The main processor 40 of each vehicle operates in the operation modeinstructed by the server 3.

The upload suppression section may be, for example, a road segment inwhich a sufficient amount of probe data necessary forgenerating/updating map data has been already collected. According tothis setting, the server 3 instructs the vehicle traveling on the roadsegment where a sufficient amount of probe data is collected to thesuppression transmission mode and uploads only the dynamic information,or only a part of feature information.

In addition, the upload suppression section may be a road segment withbad weather. According to this setting, the risk of uploading inaccurateprobe data can be reduced. The upload suppression section may bedynamically changed according to the degree of collection of probe data,the time zone, and the weather conditions. The upload suppressionsection may be determined by the server processor 31. The serverprocessor 31 may distribute the determined upload suppression sectioninformation to the vehicle, and the vehicle side may determines whetheror not the current position corresponds to the upload suppressionsection and determine the operation mode. According to such aconfiguration, it is not necessary for the server processor 31 tospecify the operation mode for each vehicle, and the processing load ofthe server processor 31 can be reduced. The main processor may beconfigured to spontaneously switch operating modes based on at least oneof the vehicle's travel area, weather conditions, and time zones. Themain processor 40 may be configured to shift from the first mode to thesecond mode based on at least one of the instruction from the server 3,the traveling area of the vehicle, the weather condition, and the timezone.

According to the suppression transmission mode, the types of informationas a reporting target are reduced as compared with the case of the fulltransmission mode. As a result, the amount of communication from thevehicle to the server 3 can be reduced for the entire system. Further,since uploading of unnecessary items can be suppressed, the load on notonly the communication equipment but also the main processor 40 and theserver processor 31 can be reduced.

In addition, when a plurality of vehicles exist in a predeterminedupload suppression section, the server processor 31 sets any one of theplurality of vehicles as the transmission assignment vehicle, and probedata is uploaded only by the transmission assignment vehicle. Accordingto such a configuration, the vehicles other than the transmissionassignment vehicle traveling in the upload suppression section does notupload the probe data. Therefore, the amount of data communication fromthe vehicle to the server 3 can be reduced for the entire system.

The transmission assignment vehicle in charge of transmission may be,for example, a vehicle having a sufficient distance from the precedingvehicle, a tall vehicle such as a truck, or the like. According to thesevehicles, it is easy to recognize feature information. Therefore, it ispossible to efficiently collect high-quality feature information.Further, the transmission assignment vehicle may be a vehiclecorresponding to the leading vehicle or a vehicle using the imageprocessor 20 having the best object recognition performance or a vehiclehaving the highest positioning accuracy by GPS among a plurality ofvehicles (hereinafter referred to as a vehicle group) constituting onegroup. The transmission assignment vehicle in charge of transmission maybe determined by the server 3 based on the position informationsequentially reported from each vehicle. Here, as another aspect, it maybe determined by each transmission assignment vehicle in charge oftransmission sharing information by vehicle-to-vehicle communication. Inthe configuration in which the server 3 appoints the transmissionassignment vehicle, under a precondition, each vehicle sequentiallyreports vehicle information such as position information, theperformance of the image processor 20, and information indicating GPSpositioning accuracy to the server 3. With the above configuration, theamount of data communication from the vehicle to the server 3 can bereduced. The vehicle group may be preferably set for each lane. A set ofvehicles in which the inter-vehicle distance is less than apredetermined threshold value can be defined as one vehicle group. Theabove configuration corresponds to a configuration such that the server3, as an operation mode, includes a collection mode in which the server3 requests all vehicles located on the road segment to transmit probedata, and a save mode in which the server 3 does not request a part ofthe vehicles to transmit probe data.

The operating mode of the server 3 may vary from road segment to roadsegment or map tile to map tile. The operation mode of the server 3 foreach road segment/map tile may be determined according to the collectionstatus of probe data for the road segment/map tile. For example, theserver 3 may operate in the collection mode for a road segment withinsufficient probe data, and may operate in a save mode for a roadsegment in which a necessary and sufficient amount of data is collected.The server 3 may update the map data in units of map tiles, or mayupdate the map data in units of road segments. When the map is updatedin units of map tiles, the above-mentioned concept of upload suppressionsection may be extended to the concept of map tiles. That is, the uploadsuppression tile corresponding to the upload suppression section may beappropriately set. Each vehicle may be configured to operate insuppression mode based on its presence in the upload suppression tile.

[Map Generation Processing]

An example of the flow when the server processor 31 generates a mapbased on the probe data transmitted to the server 3 via thecommunication module 50 will be described with reference to FIGS. 6 to8.

Here, there is a vehicle traveling in an area corresponding to a certainmap tile, and the vehicle constitutes the map system 1. That is, atleast one image representing the environment of the vehicle is acquiredby the camera 10 mounted on the vehicle, the global coordinates of thelandmarks included in the image are calculated, and the images areuploaded to the server 3.

As shown in FIG. 6, first, step S200 is executed. Step S200 is a step inwhich the server processor 31 constituting the server 3 acquires probedata. The server processor 31 acquires probe data from a plurality ofvehicles traveling on the same map tile. That is, the server processor31 acquires a plurality of coordinate data for one landmark. Probe datais sequentially uploaded to the server 3 from a plurality of vehicles.The server processor 31 stores the probe data provided by each vehiclein a state of being connected or divided into a predetermined length foreach provider.

Next, step S201 is executed. Step S201 is a step in which the serverprocessor 31 calculates the variance of the coordinates for eachlandmark and determines whether or not the calculated variance is largerthan a predetermined threshold value. The variance is calculated foreach coordinate of latitude, longitude and altitude, and each varianceis compared to a pre-specified threshold. As shown in FIG. 7, the serverprocessor 31 calculates the variance σ² of each landmark 63 based on theprobe data received from the plurality of vehicles. In the example shownin FIG. 7, four landmarks 63 a to 63 d exist in the map tile, and thevariances σ_(a) ², σ_(b) ², σ_(c) ², and σ_(d) ² are calculated for eachlandmark.

In step S201, when the variance of the coordinates of all the landmarks63 is equal to or less than a predetermined threshold value, thedetermination in this step is “NO”, and the process proceeds to stepS202.

Step S202 is a step in which the server processor 31 statisticallycalculates the coordinates of each landmark 63. When the variance of thecoordinates of each landmark 63 is equal to or less than a predeterminedthreshold value, it means that the coordinates of the landmark 63 can bedetected with a certain degree of accuracy. That is, it means that themap can be generated with relatively high accuracy even when thecoordinates of each landmark 63 are statistically calculated withoutusing the reference mark described later. In step S202, probe datareceived from a plurality of vehicles is used to perform, for example, aprocess of obtaining an average for each landmark 63, and calculateglobal coordinates. Then, this flow ends.

On the other hand, in step S201, when the variance of at least onelandmark 63 is larger than a predetermined threshold value, thedetermination is “YES”, and the process proceeds to step S203. Step S203is a step of determining whether or not high-precision positioning dataexists for the landmark 63 whose variance is larger than a predeterminedthreshold value. The high-precision positioning data is coordinate datameasured by a method different from the probe data, such as real-timekinematics (i.e., RTK) and precision independent positioning (i.e.,PPP). High-precision positioning data refers to data generated by adedicated mobile mapping system vehicle equipped with a laser radar(LiDAR), optical camera, GNSS receiver, acceleration sensor, and thelike, or positioning operations. Hereinafter, the coordinate datadetermined by precise measurement will be referred to as referencecoordinates. Further, the landmark 63 to which the reference coordinatesare given is referred to as a reference mark or a reference landmark.The reference mark plays a role as a ground reference point (GCP orGround Control Point). The reference mark is a point where theabove-mentioned high-precision positioning is performed. For example,signboards equivalent to traffic signs such as regulatory signs andguide signs, toll gates on expressways, connection points betweenexpressways and general roads, and corners (i.e., edges) of structuressuch as buildings may be used as reference marks. In addition, featurepoints such as corners of lane markings, branching/merging points withother lane markings, and ends of guardrails may also be adopted asreference marks. Points where lanes increase or decrease may also beused as reference marks. The reference mark may be preferably a fixedthree-dimensional structure. Here, as an example, a feature such as aguide sign, which is arranged at a position relatively higher than theroad surface and is arranged at a position where the camera 10 caneasily take a picture, is set as a reference mark. Hereinafter, forconvenience, features other than the reference mark will also bereferred to as normal features.

As described above, step S203 is a step of determining whether or notthe reference coordinates are assigned to the corresponding landmark 63.Here, for example, the reference coordinates exist at the landmark 63 bshown in FIG. 7 (indicated by the black-painted triangular mark in FIG.8). That is, the landmark 63 b is a reference mark. When the referencemark is present, the determination in step S203 is “YES”, and theprocess proceeds to step S204.

Step S204 is a step in which the server processor 31 matches thecoordinates of the landmark 63 b as the reference mark measured in realtime by the camera 10 and the sensor 30 with the reference coordinates.Here, the reference coordinates exist at the landmark 63 b, and, forexample, the reference coordinates are defined as Xref. When thecoordinates of the landmark 63 b on the probe data measured in real timeare defined as X, the coordinates X match the coordinates Xref. That is,it is displaced parallel by a value of “Xref−X”. By this operation, thecoordinates of the landmarks 63 b as all the reference marks recorded inthe plurality of probe data become Xref. On the other hand, as shown inFIG. 8, the coordinates of the landmarks 63 a, 63 c, 63 d other than thelandmark 63 b are also displaced parallel by a value of “Xref−X”.Although the coordinates are expressed as one dimension here forconvenience, they are actually calculated in three dimensions oflatitude, longitude, and altitude.

After step S204, step S202 is executed. The coordinates of the landmark63 b as the reference mark match the reference coordinates. Further, forthe coordinates of the other landmarks 63 a, 63 c, 63 d, for example, aprocess of obtaining an average thereof is performed to calculate globalcoordinates. Then, this flow ends.

When the reference mark does not exist in step S203, the processproceeds to step S205. Step S205 is a step in which the server processor31 sets a flag indicating that there is no reference mark. By setting aflag for the landmark 63 for which the variance larger than thethreshold value is calculated, the possibility that high-precisionpositioning is necessary can be visualized. After that, this flow ends.

By adopting the above flow, the map system 1 uses high-precisionpositioning data as reference coordinates for the landmark 63 whosecoordinate accuracy cannot be obtained only by accumulating GPS andprobe data so that coordinates can be calculated with high accuracy evenfor other landmarks 63 that do not have accurate positioning data. As aresult, the accuracy of the map tile to which the corresponding landmark63 belongs can be improved.

From the server's point of view, the above configuration corresponds tothe configuration of: acquiring probe data including observationcoordinates of a plurality of map elements associated with informationabout a traveling road segment from a plurality of vehicles; correctingthe observed coordinates of the map element included in the probe datathat includes observed coordinates of the reference mark so that theobserved coordinates of the map element defined as the reference markmatch the absolute coordinates of the reference mark or the deviationdegree from the absolute coordinates of the reference mark is minimized;and determining the coordinates of the map element by statisticallyprocessing the observed coordinates of the corrected map element.

In the above, the process for registering/updating landmark informationhas been described. Alternatively, the target of the above process canbe applied to various features (in other words, map elements) such aslane marks. The server processor 31 may be configured to update thecoordinate information of features such as landmarks and lane markingsaccording to the procedure shown in FIG. 9. The process shown in FIG. 9(hereinafter, map data update process) may be executed periodically foreach map tile, for example. For example, the process shown in FIG. 9 isexecuted every day at midnight. Of course, the process shown in FIG. 9may be executed at the timing when a predetermined number or more ofprobe data for the map tile as the process target are accumulated. Themap data may be updated for each road segment. The map data updateprocess shown in FIG. 9 includes steps T201 to T215.

First, in step T201, a plurality of probe data are provided from aplurality of vehicles traveling on the same road segment, and theplurality of probe data stored in a database (not shown) are read out,and the process proceeds to step T202. Whether or not the plurality ofprobe data are probe data for the same road segment may be determinedbased on the movement trajectory information and GPS coordinateinformation included in the probe data.

In step T202, any one of the plurality of probe data extracted in stepT201 is selected and the process proceeds to step T203. In step T203,the map data of the corresponding road segment is extracted based on thecoordinate information of various features included in the selectedprobe data, and the process proceeds to step T204.

In step T204, it is determined whether or not the probe data includes apredetermined number (for example, three) or more of reference markinformation based on the map data read out in step T203. Thepredetermined number here may be preferably 3 or more for theconvenience of the positioning process in the subsequent stage. Asanother aspect, the number of reference marks to be included may be setto 4, 5, or the like. As an example, the server processor 31 executesstep T205 when the probe data includes information of three or morereference marks. On the other hand, when the probe data includes lessthan three reference marks, step T207 is executed. In step T205, areference mark (hereinafter, common reference mark) common to the mapdata and the probe data is set, and step T206 is executed.

In step T206, the alignment process for the probe data is performedusing the common reference mark. The alignment process is a process ofcorrecting the observed position coordinates of various featuresincluded in the probe data by using the observed coordinates of thecommon reference mark and the map registration coordinates. The mapregistration coordinates here refer to the coordinates registered in thecurrent (latest) map data. The observed coordinates here are thecoordinates calculated by the vehicle and refer to the coordinatesdescribed in the probe data.

As a probe data correction method, an ICP (Iterative Closest Point)method can be adopted. The ICP method is a method in which parallelmovement and rotation of each point group are repeated so that the twopoint groups are most consistent as a whole. Specifically, the methodincludes: a step of searching and associating the nearest point in theother point group (hereinafter, the second point group) from each pointin the point group on one side (hereinafter, the first point group); anda step of adjusting the position and orientation of the coordinatesystem of each point group so as to minimize the difference between theassociated points. As a method of calculating a vector for rotating anddisplacing parallel each point group, SVD (Singular ValueDecomposition), the steepest descent method, or the like can be adopted.According to SVD, it is possible to obtain a rotation matrix and aparallel displacement vector for bringing a certain point group closerto a target point group (for example, an average point group of a firstpoint group and a second point group). Further, according to thesteepest descent method, the minimum value of the function representingthe mean square error of the distance between the corresponding pointscan be searched, and the rotation matrix and the parallel displacementvector can be obtained.

The method of correcting the position coordinates of the featuresincluded in the probe data based on the position coordinates of thecommon reference mark may not be limited to the above method. As thecorrection method for the probe data, the correction method described inJapanese Patent Application No. 2018-163076, which is separately filed,may be adopted. That is, the center of gravity point of the observedcoordinates of the common reference mark (hereinafter referred to as thefirst center of gravity point) is calculated, and a plurality of commonreference marks are planar approximated by, for example, the leastsquares method. Then, the normal vector (hereinafter, the first normalvector) with respect to the approximate plane is calculated. Further,the server processor 31 calculates the center of gravity point(hereinafter, the second center of gravity point) of the mapregistration coordinates of the common reference mark, and alsocalculates the approximate plane corresponding to the common referencemark. Then, the normal vector (hereinafter, the second normal vector)with respect to the approximate plane is calculated. Next, the positioncoordinates of the feature in the probe data are translated in parallelso that the first center of gravity point coincides with the secondcenter of gravity point. In addition, the position coordinates of eachobject in the probe data are rotated so that the first normal vectorcoincides with the second normal vector. Then, the position coordinatesof the feature in the probe data are rotationally moved around the firstnormal vector passing through the first center of gravity so that thesum of squares of the errors of the common reference mark is minimized,and the alignment process is completed.

The server processor 31 acquires probe data corrected for the positionand orientation of the feature by completing the alignment process. Suchan alignment process corresponds to a process of correcting the positioncoordinates of various features included in the probe data based on theposition coordinates of the common reference mark. The observationcoordinates of the normal feature related to the observation coordinatesof a certain reference mark refer to the observation coordinates of thenormal feature detected and uploaded by the same vehicle. In otherwords, the observed coordinates of a normal feature associated with areference mark refer to the observed coordinates of a normal featureprovided by the vehicle that provides the observed coordinates of thereference mark.

In step T207, the alignment process for the selected probe data isomitted, and the process proceeds to step T208. The probe data includingless than three reference marks may be preferably excluded from thetarget of the integration process described later. Alternatively, theserver processor 31 may be configured to divide/connect the variousprobe data into data having a length that includes 3 or 4 or morereference marks. In step T209, it is determined whether or notunprocessed probe data remains in the probe data read out in step T201.When unprocessed probe data remains, the process proceeds to step T209,and the processes after step T203 are executed for unprocessed probedata. On the other hand, when there is no unprocessed probe data, stepT210 is executed.

In step T210, the corrected probe data integration process is performed.The probe data integration process is a process of statisticallycalculating the coordinates of the feature, as in S201. For example, thevariance of the coordinates of each feature is calculated, and when thevariance is less than a predetermined threshold value, the median/meanvalue is adopted as the coordinates of the feature. Further, for afeature whose variance is equal to or higher than a predeterminedthreshold value, for example, a verification flag is set. Theverification flag corresponds to a flag indicating that the data isuncertain to be registered as a map. The server processor 31 maycalculate the coordinates for each landmark after excluding deviatedvalues so that the variance becomes equal to or less than apredetermined threshold value during the probe data integration process.Moreover, the evaluation of the variance in the integrated processingmay not be essential and may be omitted. By the above processing, theposition coordinates of each object are statistically determined afterbeing corrected by using a predetermined reference landmark. Forexample, the server processor 31 corrects the coordinates of the lanemark included in each probe data by using a predetermined referencelandmark, and then statistically processes a plurality of coordinateinformation to determine the position coordinates of the lane mark.

In the following step T211, the change point is detected by comparingthe data indicating the statistical position coordinates of each object(hereinafter, integrated data) generated in step T210 with the map data.The integrated data itself or the map data reflecting the contents ofthe integrated data corresponds to the provisional map data. The changepoint here refers to a part of the integrated data that differs from thecurrent map data and indicates a place where the feature may have beenrelocated, added, or deleted. For example, among the features includedin the integrated data, the amount of deviation with respect to theposition coordinates in the map data and the statistically determinedposition coordinates are calculated for the features that have landmarkscorresponding to the current map data (that is, existing features).Then, when the deviation amount of the position coordinates exceeds apredetermined error range, it is detected as a feature suspected ofbeing relocated. Here, as an example, when the deviation amount of theposition coordinates is within a predetermined error range (for example,less than 3 cm), it is regarded as an observation error and is notdetected as a change point of the map. According to such aconfiguration, it is possible to reduce the possibility that the mapdata is frequently updated due to the observation error. Of course, asanother aspect, a deviation of 1 cm or more may be detected as a changepoint. The amount of error allowed can be changed as appropriate.

In addition, features that are included in the integrated data and arenot registered in the map data are detected as features that may havebeen newly created. In addition, features that are registered in the mapdata and are not included in the integrated data are detected asfeatures that may have been deleted. When the process in step T211 iscompleted, step T212 is executed.

In step T212, the validity of the change point is determined. When thenumber of probe data providing the feature detected as a change point isequal to or greater than a predetermined threshold value, or when it iscontinuously detected for a predetermined period (for example, 3 days),it is determined that the change point is not temporary, but it isappropriate so that the change point is reflected in the map data.Further, when the deletion of the lane marking is detected as a changepoint, it is determined whether or not the deletion section is, forexample, less than a predetermined distance (for example, 5 meters).Since the lane markings are usually extended continuously, thepossibility that only a part of the section is deleted is small. Inaddition, if an object (vehicle, puddle, snow) is temporarily present onthe lane marking, the lane marking may not be detected. That is, whenthe deleted section is less than a predetermined distance, for example,it is highly possible that the originally existing lane marking is notdetected due to a temporary event such as parking on the street, snowcover, or rainfall. By introducing the above determination logic, it ispossible to reduce the risk of erroneously determining that the lanemarkings have been deleted although the actual lane marking are notdeleted. As a result, the risk of erroneously updating the lane lineinformation of the map data can be reduced.

When a change point is detected over a wide area, such as when thedeleted section is longer than a predetermined distance, it may bedetermined that the change point has been changed (that is, appropriate)due to road construction or the like. In addition, at the change point,when the construction information indicating that the construction wascarried out within the latest predetermined period (for example, within3 days) can be acquired from an external server or detected from theprobe data, it may be determined that the change point is appropriate.The above idea can be applied not only to lane markings but also toother features such as signboards. The change points judged to be validare reflected in the map data (at step T215). In addition, for changepoints that are judged to be invalid, measures such as suspending theupdate or setting a verification flag are taken. According to theconfiguration that is configured to judge the validity of the changepoint based on the duration and scale of the change point and thepresence or absence of construction information in the vicinity of thechange point, the risk of updating the contents of the map dataerroneously due to temporary factors can be reduced.

The above description discloses a mode in which the position coordinatesof various features are calculated by integrating multiple probe dataafter aligning each feature using a reference mark for each probe data.The procedure for calculating the coordinates of the positions offeatures may not be limited to this. Instead of correcting thecoordinates of features in each probe data unit, it may be configured togenerate integrated data that statistically calculates the positioncoordinates of each feature, and then correct the coordinate informationof each feature based on the reference mark.

For example, the server processor 31 statistically obtains thecoordinates of each feature by the method described in S201 or step T210based on the plurality of probe data as the next step of the probe datareading out process corresponding to step T201. At that time, the serverprocessor 31 may be configured to adjust the observation data to be usedso that the variance is equal to or less than a predetermined thresholdvalue. The statistically calculated coordinates correspond to therepresentative observation coordinates. The representative observationcoordinate refers to the average value or the median value of aplurality of observation coordinates. Next, the server processor 31corrects the representative observation coordinates of various landmarksincluded in the integrated probe data based on the coordinateinformation of the reference mark. As the method of correction, the samemethod as in step T206 can be used. Even with such a configuration, theaccuracy of the coordinates of each object can be improved.

The map system 1 that generates and distributes the traveling trajectorymodel as map data may be configured to handle the traveling trajectorydata included in the probe data as a map element for generating thetraveling trajectory model. For example, the server processor 31 maycorrect the traveling trajectory of each vehicle by using the referencemark associated with the traveling trajectory, and then integrate andprocess a plurality of corrected traveling trajectory data to obtain atraveling trajectory model. According to the configuration in which eachtraveling trajectory is corrected using the reference mark and thenintegrated to generate a traveling trajectory model, it is possible togenerate a traveling trajectory for autonomous driving with higheraccuracy. Here, the server processor 31 may be configured to generate atraveling trajectory model obtained by averaging the travelingtrajectories of a plurality of vehicles, and then correct the travelingtrajectory model by using a reference mark. The various processesdescribed above may be configured to be shared and executed by aplurality of servers/processors. For example, the probe data integrationprocess may be configured to be performed by a server different from theserver that acquires and corrects the probe data.

The map system 1 described above corresponds to a system that correctsthe observation coordinates of the same feature provided by a pluralityof vehicles by using the observation coordinates of the reference markand the map registration coordinates, and also statistically processes(for example, averages) the corrected observation coordinates of thefeature so as to determine the coordinates of the feature. A pluralityof observation coordinates for the same feature may be provided by aplurality of different vehicles, or may be generated by the same vehiclepassing through the same point multiple times. The observationcoordinates of various features included in the probe data are correctedso that the observation coordinates of the reference mark match theabsolute coordinates of the reference mark as the map registrationcoordinates. Alternatively, the means of the matching here is notlimited to the perfect. Alternatively, approximate match may be alsoincluded. The above correction may be performed so that the degree ofdeviation between the observation coordinates of the reference mark andthe absolute coordinates is minimized. The correction process describedabove may be executed in units of road segments or in units of maptiles.

[Vehicle Control Mode Based on Map Accuracy]

Since the coordinates of the landmark 63 included in the map tile arecalculated based on a plurality of probe data, there may be statisticalvariation. The map system 1 assigns an accuracy level based onstatistical variability for each map tile. Then, the application thatuses the map information is restricted according to the accuracy level.The operation flow of the map system 1 will be described with referenceto FIG. 10.

As shown in FIG. 10, first, step S300 is executed. Step S300 is a stepin which the server processor 31 constituting the server 3 acquiresprobe data. The server processor 31 acquires probe data from a pluralityof vehicles traveling on the same map tile. That is, the serverprocessor 31 acquires a plurality of coordinate data for one landmark.

Next, step S301 is executed. Step S301 is a step in which the serverprocessor 31 calculates the coordinate variance for each landmark. Thevariance is calculated for each coordinate of latitude, longitude andaltitude. As shown in FIG. 7, the server processor 31 calculates thevariance σ² of each landmark 63 based on the probe data received fromthe plurality of vehicles. In the example shown in FIG. 7, fourlandmarks 63 a to 63 d exist in the map tile, and the variances σ_(a) ²,σ₂ ², σ_(c) ², σ_(c) ², and σ_(d) ² are calculated for each landmark.

Next, step S302 is executed. Step S302 is a step in which the serverprocessor 31 calculates the median value p of the calculated variancesσ_(a) ², σ₂ ², σ_(c) ², and σ_(d) ² and compares it with thepredetermined threshold value T1. Here, the median value of the varianceis calculated as an example, and any value may be used as long as it canstatistically index the degree of variation in the coordinates of thelandmarks belonging to the map tile. For example, the average value maybe used. When the median value p satisfies the relationship of 0<p≤T1with the predetermined threshold value T1, the determination in stepS302 is “YES”, and the process proceeds to step S303.

Step S303 is a step of assigning the accuracy level of “High” to the maptile that is determined to be “YES” in step S302. The map tile to whichthe accuracy level of “High” is given is the map tile determined to havethe highest accuracy.

On the other hand, when the determination is “NO” in step S302, theprocess proceeds to step S304. Step S304 is a step in which the serverprocessor 31 calculates the median value p (or which may be an averagevalue) and compares it with the predetermined threshold values T1 andT2. When the median value p satisfies the relationship of T1<p≤T2 withthe predetermined threshold values T1 and T2, the determination in stepS304 is “YES”, and the process proceeds to step S305.

Step S303 is a step of assigning the accuracy level of “Middle” to themap tile that is determined to be “YES” in step S302.

On the other hand, when the determination is “NO” in step S304, theprocess proceeds to step S306. Step S306 is a step of assigning theaccuracy level “Low” to the map tile for which the “NO” determination ismade in step S304. The map tile to which the accuracy level of “Low” isgiven is the map tile determined to have the lowest accuracy.

The accuracy level of the map tile is higher in the order of “High”,“Middle”, and “Low”. The higher the accuracy level, the more accuratelythe current position of the vehicle can be determined, and more advanceddriving support can be realized. That is, while traveling in an areacorresponding to a map tile having a high accuracy level, it can be usedfor advanced driving support such as autonomous driving. On the otherhand, while driving in an area corresponding to a map tile with a lowaccuracy level, the application is restricted so that it is not used forautomatic driving. More specifically, the main processor 40 allows theautomatic driving application to use the map data of the map tile whoseaccuracy level is set to the highest level. For map data of map tilesset to a low level of the accuracy level, the automatic drivingapplication is prohibited from using the map data. As a result, the maptiles obtained with high accuracy can be effectively used, and the maptiles with low accuracy can be prevented from being accidentally usedfor applications requiring more safety such as an automatic drivingapplication. When the use of the application is restricted due to theaccuracy level of the map tile, it may be preferable that the mainprocessor 40 notifies the user via the HMI 60 to that restriction.Prohibiting the provision of map data to an application indirectlycorresponds to prohibiting of the execution of the application itself ordegenerating of the function.

[Alternative Means of Satellite Positioning System]

When identifying the position of the own vehicle, the map system 1identifies the rough position of the own vehicle by positioning with asatellite such as GPS, and determines the detailed position of the ownvehicle based on the map information downloaded from the server 3 andthe coordinates of the landmark 63 calculated from the image captured inreal time by the vehicle. However, there are situations where it isdifficult to specify the position by the satellite since the vehicle isin a tunnel or between tall buildings.

As the positioning sensor 30 a, the map system 1 can employ, forexample, a radio wave detector that detects the radio wave intensityprovided in the wireless LAN. Positioning by radio waves emitted from awireless LAN base station (i.e., an access point) corresponds to analternative positioning means. Among the base stations that transmit theradio waves of the wireless LAN, the vehicle receives one of the radiowaves whose global coordinates where the base station is installed areknown. As a result, the position of the own vehicle is estimated basedon the coordinates of the base station and the intensity of the receivedradio wave. The operation flow of the map system 1 will be describedwith reference to FIG. 11.

As shown in FIG. 11, first, step S400 is executed. Step S400 is a stepin which the main processor 40 compares the reception intensity of radiowaves from GPS satellites with a predetermined threshold value. As thethreshold value, for example, the radio wave intensity of GPS isdetermined as the threshold when the position of the own vehicle can besufficiently specified by the positioning by GPS and the map informationobtained by downloading. When the reception intensity of the radio wavefrom the GPS satellite is larger than this threshold value, this step isdetermined to be “YES”, and the process proceeds to step S401. That is,the radio wave detector of the wireless LAN radio wave is invalidated asan alternative positioning means. Then, the process proceeds to stepS402, and the position of the own vehicle is specified by thepositioning by GPS and the map information obtained by downloading.Further, the map information such as the landmark 63 obtained by thecamera 10 is uploaded to the server 3. After the position of the ownvehicle is specified, the position of the own vehicle is used fordriving support such as automatic steering.

On the other hand, in step S400, when the reception intensity of theradio wave from the GPS satellite is equal to or less than thisthreshold value, the determination in this step is “NO”, and the processproceeds to step S403. That is, the radio wave detector of the wirelessLAN radio wave is validated as an alternative positioning means. Then,the process proceeds to step S404.

Step S404 is a step of determining, by the main processor 40, thesecurity level of the base station which emits radio waves of thewireless LAN. The security level is an index of trust in the informationemitted by the base station. When the security level is high, the mainprocessor 40 relies on the coordinates of the installation location ofthe base station, and specifies the current position of the own vehiclebased on the global coordinates of the base station, the receptionstrength of the radio waves received by the radio wave detector mountedon the vehicle, and the position prediction of the own vehicle by theSfM. For example, the distance from the base station is estimated basedon the reception strength, and it is determined that the distance fromthe base station installation position is within the estimated distance.When signals from multiple base stations can be received, the distanceto each base station is estimated based on the reception strength of thesignals from each base station, and the current position is calculatedusing the installation position of each base station and the distancefrom each base station. Position estimation methods using radio wavesemitted by base stations include various method such as the AOA (i.e.,Angle Of Arrival) method, which uses the direction of arrival of radiowaves, the arrival time (TOA or Time of Arrival) method, and the arrivaltime difference (TDOA or Time Difference of Arrival). The security levelcan be set arbitrarily. For example, it can be inferred that thesecurity level may be high for base stations provided by publicinstitutions and public infrastructure companies. On the other hand, itcan be inferred that the security level of a base station provided by anindividual may be low.

When it is determined in step S404 that the security level of the basestation or the security level of the alternative positioning means islow, this step is determined to be “NO”, and the process proceeds tostep S405. In step S405, the map information such as the landmark 63obtained by the camera 10 is uploaded to the server 3. When the GPSreception strength is sufficiently secured or the positioning by thealternative positioning means having a high security level is realized,the positioning information by the alternative positioning means isutilized for specifying the position of the own vehicle as in step S402.On the other hand, when only positioning by an alternative positioningmeans having a low security level can be realized, the position of theown vehicle is not specified, and the positioning information isprovided only by uploading the map information to the server 3.

The step of determining the level of security of the alternativepositioning means is optional and is not always necessarily performed.That is, step S404 in FIG. 11 may not be performed. In such an aspect,when positioning by satellite cannot be sufficiently performed andpositioning is performed by an alternative positioning means, it may bepreferable that the positioning information is provided only byuploading the map information to the server 3.

By the way, the alternative positioning means may not be limited to thepositioning by the radio wave emitted from the wireless LAN base stationwhose installation position coordinates are known. Alternatively, thepositioning by the radio wave emitted from the short-range wirelesscommunication base station whose installation position coordinates areknown, the positioning by IMES, the positioning by geomagnetism, and thelike may be adopted.

The radio wave detector that receives radio waves from wireless LAN,short-range wireless communication, and IMES, and the magnetic detectorthat detects geomagnetism may not necessarily be fixed to the vehicle.For example, when a mobile device such as a smartphone is equipped witha detector as described above and the mobile device is linked to the mapsystem 1, the positioning information obtained by the mobile device isused for the map system 1.

[Method for Updating Map Data]

When identifying the position of the own vehicle, the map system 1identifies the rough position of the own vehicle by positioning with asatellite such as GPS, and determines the detailed position of the ownvehicle based on the map information downloaded from the server 3 andthe coordinates of the landmark 63 calculated from the image captured inreal time by the vehicle. However, there are situations in which the mapinformation does not exist on the server 3 or the map information is oldand the current situation is not accurately reflected.

Based on such circumstances, three modes of “no map”, “map exists butold”, and “latest map exists” are set for each map tile. The update flagmay be set on the map tile for the two modes of “no map” and “map existsbut old”. Map tiles corresponding to the area where the update flag isset may be preferentially to generate a map or to updated the map. Theoperation flow of the map system 1 corresponding to the technical ideawill be described with reference to FIG. 12.

As shown in FIG. 12, first, step S500 is executed. Step S500 is a stepin which the main processor 40 identifies a rough position of the ownvehicle by GPS or the like. By this step, the area where the own vehicleexists is grasped.

Next, step S501 is executed. Step S501 is a step in which the mainprocessor 40 determines whether or not the map information of the maptile corresponding to the area where the own vehicle exists is stored inthe server 3. For example, the main processor 40 transmits the currentposition information of the own vehicle to the server 3. When the mapinformation of the map tile of the area where the vehicle exists, theserver 3 returns a signal indicating that the map information exists.When the server 3 does not have the map tile of the area where thevehicle exists, the server 3 returns a signal indicating that the server3 does not have the map data of the requested area. As described above,step S501 may be performed by coordinating with the main processor 40and the server 3. When the map information is not stored as a map tile,this step is determined as “NO”, and the process proceeds to step S502.When there is no map data of the map tile in which the vehicle exists,the case where the map data of the map tile has expired is alsoincluded.

Step S502 is a step in which the main processor 40 sets the map tilecorresponding to the area to be the “no map” mode. Then, the processproceeds to step S503.

Step S503 is a step in which the main processor 40 sets the update flagto be “ON” for the map tile corresponding to the area. When the updateflag is set to “ON”, the main processor 40 sequentially uploads featureinformation such as lane line information as probe data. As a result,for the map tile corresponding to the area in which the update flag isset to “ON”, the map is preferentially generated by the server processor31. This flow ends through step S503. As a more preferred embodiment,the main processor 40 uploads vehicle behavior information in additionto feature information while traveling on the map tile in which theupdate flag is set to “ON”.

In step S501, when the map information exists in the map tilecorresponding to the area where the own vehicle exists, this step isdetermined to be “YES”, and the process proceeds to step S504.

Step S504 is a step of determining whether or not the latest informationis publicly disclosed with respect to the map information recorded onthe map tile. In the case of Japan, public disclosure is, for example,map information released by the Geographical Information Authority ofJapan in the Ministry of Land, Infrastructure, Transport and Tourism.Here, when the difference between the landmark coordinates in the mapinformation stored in the server 3 and the landmark coordinates in themap information published by the Geographical Information Authority ofJapan is a predetermined distance (for example, 10 cm) or more, it isdetermined that the latest information is publicly available. Inaddition to the map information provided by the Geospatial InformationAuthority of Japan, map information provided by a certain map vendor mayalso be used as public map information. Public disclosure may not belimited to disclosure by government agencies, but also includesemi-public disclosure by designated map vendors. In addition, even whenit is not made public, the difference between the coordinates of thelandmarks in the map information stored in the server 3 and thecoordinates of the measured landmarks is equal to or larger than apredetermined distance (for example, 10 cm) by the fixed point surveyinginstrument owned by the Geospatial Information Authority of Japan, orhigh-precision GPS positioning, and the like, it is determined that thelatest information is publicly disclosed. In such a case, thedetermination in this step is “YES”, and the process proceeds to stepS505. The step S504 may be performed by either the vehicle or theserver. The main processor 40 or the server processor 31 communicateswith an external server managed by a map vendor or a government agencyto determine whether or not the latest map information is published forthe map tile in which the vehicle exists.

Step S505 is a step in which the main processor 40 sets the map tilecorresponding to the area to be the “map exists but old” mode. Then, theprocess proceeds to step S503.

Step S503 is a step in which the main processor 40 sets the update flagto be “ON” for the map tile corresponding to the area. As for the maptile corresponding to the area where the update flag is set to “ON”, thefeature information is sequentially uploaded from the vehicle to theserver 3, so that the map is updated preferentially. This flow endsthrough step S503.

When it is determined in step S504 that the latest information is notpublicly disclosed with respect to the map information recorded in themap tile, this step becomes a NO determination and proceeds to stepS506.

Step S506 is a step in which the main processor 40 downloads the mapinformation of the map tile corresponding to the current position fromthe server 3.

Next, step S507 is executed. In step S507, the main processor 40verifies the coordinates of the landmark 63 included in the mapinformation downloaded from the server 3 with the coordinates of thelandmark 63 calculated based on the image captured in real time, so thatthe position of the subject vehicle is identified (that is, localized).

Next, step S508 is executed. Step S508 is a step of determining whetheror not the main processor 40 has detected a deviation in the coordinatesof the own vehicle (hereinafter, also referred to as a positionaldeviation).

The position of the own vehicle specified based on the coordinates ofthe landmark 63 included in the map information downloaded from theserver 3 and the relative coordinates of the landmark 63 with respect tothe own vehicle position calculated from the image captured in real timeby the camera 10 is referred to as the first position. On the otherhand, the position of the own vehicle specified by using the GPS radiowave that does not depend on the map information stored in the server 3is referred to as a second position. The means for calculating thecoordinates of the landmark 63 in real time may not be limited to thatby the camera 10, and for example, a radar or LiDAR may be used.Further, the means for identifying the position of the own vehiclewithout depending on the map information may not be limited to GPS, forexample, odometry, dead reckoning, wireless LAN or short-range wirelesscommunication, position identification using IMES radio waves, andgeomagnetism may be adopted as an identifying means.

The detection of the deviation of the coordinates of the own vehiclemeans that, for example, it is detected that the deviation between thefirst position and the second position is equal to or greater than apredetermined distance. Alternatively, the detection of the deviation ofthe coordinates of the own vehicle indicates that a state in which thedeviation between the first position and the second position is equal toor greater than a predetermined distance has occurred a predeterminednumerical number of times. The numerical number of times and frequencyof misalignments of the positioning correspond to index information (inother words, an error signal) indicating that the map data needs to beupdated. In addition, the position misalignment corresponds to an eventfor transmitting index information (hereinafter referred to as atransmission event). The position deviation detection (in other words,the detection of the transmission event) may be performed by the mainprocessor 40 itself or by another device (for example, the imageprocessor 20). When another device detects it, the main processor 40 maydetect that the position misalignment (in other words, a transmissionevent) has occurred by inputting a signal indicating that the positionmisalignment has occurred from the device.

Another example of detecting the coordinate deviation of the own vehiclemay be a determination such that the deviation of the coordinates of theown vehicle is detected when the driver's steering intervention occurswith a predetermined amount or at a predetermined frequency whiledriving assistance such as automatic driving or lane keeping is executedusing map information. A point where the driver's steering/decelerationoperation intervenes when driving assistance such as automatic drivingor lane keeping is being executed using map information is also definedas an inconsistence point. Similar to the steering intervention, thespeed adjustment intervention such as depressing the brake pedal canalso be adopted as a judgment index for the occurrence of positionmisalignment. The amount and frequency of operation interventions suchas steering intervention and deceleration operation by the drivercorrespond to index information indicating that the map data needs to beupdated. Further, the driver's operation intervention during automaticdriving corresponds to an event for transmitting index information tothe server 3.

When the position shift of the own vehicle is detected in step S508, thedetermination in this step is “YES” and the process proceeds to stepS505. It may be configured such that the number of times themisalignment is detected is counted up, and when the number of times themisalignment is detected exceeds a predetermined threshold value, stepS508 is determined to be “YES” and step S505 is executed.

As described above, step S505 is a step of setting the map tilecorresponding to the area to the “map exists but old” mode, and then theupdate flag is set to “ON” through step S503. The state in which theposition misalignment of the own vehicle is detected may be assumed to asituation in which the land form or the position of the landmark 63 haschanged before the information is officially updated due to, forexample, a natural disaster. By setting the update flag to “ON” throughstep S508, it may be possible to promote the update of the mapinformation stored in the server 3 prior to the official map update.

On the other hand, when the position deviation of the subject vehicle isnot detected, the determination in step S508 is “NO”, and the processproceeds to step S509.

Step S509 is a step in which the main processor 40 sets the map tilecorresponding to the area to be the “latest map exists” mode. Then, theprocess proceeds to step S510.

Step S510 is a step in which the main processor 40 sets the update flagto be “OFF” for the map tile corresponding to the area. Map tilescorresponding to areas where the update flag is set to “OFF” do notrequire the latest map update and can be actively used for drivingsupport and the like. This flow ends through step S510. When the updateflag is set to “OFF”, the main processor 40 uploads vehicle behaviorinformation without sending feature information such as lane lineinformation as probe data. According to the configuration for uploadingvehicle behavior information, the server 3 can detect the occurrence oftraffic congestion and the like.

As described above, the main processor 40 sets one of the three modes of“no map” mode, “exists but old” mode and “the latest map exists” modefor the map tile corresponding to the area where the own vehicle exists,based on the predetermined conditions related to step S501, step S504,and step S508, and sets the update flag corresponding to each mode. Formap tiles with “no map” mode and “map exists but old” mode, the updateflag is set to “ON”, so that the updating or generating map informationincluded in the map tile can be executed preferentially.

In the above, the configuration for determining the necessity ofupdating the map data on the vehicle side has been disclosed, but theconfiguration may not be limited to this feature. The server 3 maydetermine whether or not the map data of each map tile needs to beupdated based on the probe data from a plurality of vehicles. Forexample, when the main processor 40 detects a position misalignment oran occupant's operation intervention for the automatic driving of thevehicle in step S508, the processor 40 reports the detection to theserver 3. Alternatively, a signal indicating that the update isnecessary is transmitted to the server 3.

The server processor 31 sets the update flag of the map tile, in whichthe number of times the misalignment is detected exceeds a predeterminedthreshold value, to “ON”. Then, the vehicle traveling in the area wherethe update flag is set to “ON” is requested to transmit the probe dataincluding the feature information. Even with such a configuration, themap data can be updated quickly. The unit of updating the map data maynot be limited to the map tile unit. The necessity of renewal may bemanaged for each road segment. For example, ON/OFF of the update flagmay be set for each road segment.

Further, the map data generated/updated based on the probe data may beprovisionally distributed to each vehicle as temporary map data. Theprovisionally distributed map is verified, for example, whether it canbe used for automatic control in a plurality of vehicles. For example,the main processor 40 of each vehicle verifies the temporary map basedon whether or not the position shift is detected when the position ofthe own vehicle is calculated using the temporary map data, whether ornot the driver's operation intervention is performed, and so on. Thetentative map data may be verified based on whether or not the travelingtrajectory planned based on the image recognition result and thetraveling track planned using the tentative map match. It may bepreferable that the provisional map data is not used for actualautomatic driving until the verification is completed and it becomes theofficial map data. As the method for verifying the provisional map data,the method described in Japanese Patent Application No. 2018-163077,which is separately applied for, may be used. When each vehicledetermines that there is no difficulty as a result of verifying theprovisional map data, it reports the determination to the server 3. Whenit is determined that the temporary map data has a difficulty, itnotifies the server 3 of the difficulty. The server 3 finally determineswhether there is a difficulty with the temporary map data based on theverification results of a plurality of vehicles, and when it isdetermined that there is no difficulty, the server 3 adopts thetemporary map data as the official map. The map data adopted as theofficial map will be distributed to each vehicle. The vehicle to whichthe temporary map data has been distributed may be notified that thetemporary map data is used as the official map data.

In the map system 1, the update flag indicating that the map informationneeds to be updated is set based on a predetermined condition determinedin advance, so that it is possible to clearly distinguish whether or notthe map information needs to be updated. It may be particularlyeffective when the coordinates of the landmark 63 suddenly change due toa natural disaster or the like.

[Countermeasure when a Landmark Cannot be Detected]

When identifying the position of the own vehicle, the map system 1identifies the rough position of the own vehicle by positioning with asatellite such as GPS, and determines the detailed position of the ownvehicle based on the map information downloaded from the server 3 andthe coordinates of the landmark 63 calculated from the image captured inreal time by the vehicle. However, there may be obstacles around the ownvehicle that hinder the imaging of the landmark 63, and there may besituations in which the coordinates of the landmark 63 cannot bespecified.

The map system 1 may control the behavior of the vehicle so that, whenthe own vehicle is in the above situation, there is at least onelandmark 63 that is not obstructed by obstacles within the angle of viewof the camera 10 that is an imaging device. Here, the operation flow ofthe map system 1 based on the technical idea will be described withreference to FIG. 13. Here, as an example, a camera 10 installed forphotographing the environment in front of the vehicle will be describedas an example. In addition to the camera 10 that monitors the front, arear camera that is responsible for rear monitoring and a camera 10 thatis responsible for side monitoring (that is, a left/right camera) may bearranged together. Further, the preceding vehicle will be described asan example of an obstacle blocking the landmark 63. Here, the obstaclemay be a following vehicle corresponding to the rear monitoring camera10 or a parallel running vehicle corresponding to the side monitoringcamera 10. Objects other than vehicles may act as obstacles. As theperipheral monitoring sensor constituting the map system 1, a part orall of the front camera, the rear camera, and the side camera can beadopted. A rear camera that captures a predetermined rear rangecorresponds to a rear monitoring device.

As shown in FIG. 13, first, step S600 is executed. Step S600 is a stepin which the main processor 40 identifies a rough position of the ownvehicle by GPS or the like. By this step, the area where the own vehicleexists is grasped.

Next, step S601 is executed. Step S601 is a step in which the mainprocessor 40 detects the preceding vehicle based on the image capturedby the camera 10.

Next, step S602 is executed. Step S602 is a step in which the mainprocessor 40 acquires the vehicle type of the preceding vehicle. Thevehicle type is recorded in a database stored in the memory 80 or theserver 3, and the type is determined from the silhouette information ofthe target obtained from the image and the like.

Next, step S603 is executed. Step S603 is a step in which the mainprocessor 40 acquires the vehicle height of the preceding vehicle thatbecomes an obstacle based on the vehicle type. The vehicle heightinformation is linked to the vehicle type, and the vehicle heightcorresponding to the vehicle type of the preceding vehicle is acquired.The vehicle height information may be calculated from the capturedimage.

Next, step S604 is executed. Step S604 is a step in which the mainprocessor 40 determines whether or not the preceding vehicle as anobstacle is a tall vehicle. In the determination of whether or not thepreceding vehicle is a tall vehicle, for example, the vehicle heightacquired in step S603 is compared with a predetermined threshold value,and when the vehicle height is higher than the threshold value, it isdetermined that the preceding vehicle is a tall vehicle.

Alternatively, in another example, the vehicle type classified as a tallvehicle may be determined in advance, and when the preceding vehicle isthe corresponding vehicle type, it may be determined to be a tallvehicle. When determining whether or not the vehicle is tall accordingto the vehicle type, step S603 for acquiring the vehicle height can beomitted. The vehicle type determined to be a tall vehicle includes, forexample, a truck or a fire engine. When it is determined in step S604that the preceding vehicle is a tall vehicle, the process proceeds tostep S605.

Step S605 is a step in which the main processor 40 controls the actuator70 to change the relative position between the own vehicle and theobstacle so that the landmark 63 can be recognized by the camera 10.Specifically, for example, the actuator 70 is a braking device, and themain processor 40 drives the braking device to brake the own vehicle. Asa result, the distance between the own vehicle and the precedingvehicle, which is an obstacle, becomes large, and the area occupied bythe preceding vehicle with respect to the angle of view becomes small.Therefore, since it is possible to realize a situation in which thelandmark 63 such as a sign is easily reflected within the angle of view,the main processor 40 can recognize the landmark 63 and can calculatethe coordinates of the landmark 63. When the preceding vehicle is a tallvehicle, the traffic light, the destination display, and the like arelikely to be blocked by the preceding vehicle and the camera 10 cannotbe recognized. Therefore, the detection frequency of the landmark 63 isimproved by going through step S605. Along with this, the frequency ofcalculation of the coordinates of the landmark 63 from the image is alsoimproved, so that the coordinates of the landmark 63 held by the mapinformation can be checked for a longer period of time, and the positionof the own vehicle can be specified more accurately. Control thatincreases the distance between the vehicle and the preceding vehicle bydeceleration or the like corresponds to an example of vehicle controlthat makes it easier for the peripheral monitoring sensor to detectlandmarks.

The actuator 70 controlled by the main processor 40 may not be limitedto the braking device, and may be, for example, a steering operation.Specifically, when the preceding vehicle is a tall vehicle, the mainprocessor 40 may control the steering to change lanes to create asituation in which there is no preceding vehicle that becomes anobstacle in front of the own vehicle.

After step S605, this flow ends. Further, in step S604, when it isdetermined that the preceding vehicle is not a tall vehicle, this flowis similarly terminated.

By adopting the above configuration, the map system 1 also improves thecalculation frequency of the coordinates of the landmark 63 from theimage, so that it is possible to verify with the coordinates of thelandmark 63 held by the map information for a longer period of time sothat the position of the own vehicle can be specified more accurately.

Countermeasure when Landmark Cannot be Detected (Modification Example)

In the above, an example of acquiring the vehicle type of the precedingvehicle, which is an obstacle, and controlling the vehicle based on thevehicle type has been described. As another aspect, the map system 1 maycontrol the vehicle so that the landmark 63 can be recognized based onthe inter-vehicle distance measured in real time and the vehicle heightcalculated by image recognition. An operation example of the map system1 based on the technical idea will be described with reference to FIGS.14 to 16. Here, a camera 10 installed for capturing an image of theenvironment in front of the vehicle will be described as an example. Inaddition to the camera 10 that monitors the front, the camera 10 that isresponsible for rear monitoring and side monitoring may coexist.Further, the preceding vehicle will be described as an example of anobstacle blocking the landmark 63. Here, the obstacle may be a followingvehicle corresponding to the rear monitoring camera 10 or a parallelrunning vehicle corresponding to the side monitoring camera 10.Obstacles may also be objects other than vehicles.

As shown in FIG. 14, first, step S700 is executed. Step S700 is a stepin which the main processor 40 identifies a rough position of the ownvehicle by GPS or the like. By this step, the area where the own vehicleexists is grasped.

Next, step S701 is executed. Step S701 is a step in which the mainprocessor 40 detects the preceding vehicle based on the image capturedby the camera 10.

Next, step S702 is executed. Step S702 is a step in which the mainprocessor 40 measures the distance to the preceding vehicle, that is,the inter-vehicle distance. The inter-vehicle distance can be measuredby radar, LIDAR, or a fusion configuration of them and an imagingdevice.

Next, step S703 is executed. Step S703 is a step in which the mainprocessor 40 measures the height of the preceding vehicle. The height ofthe preceding vehicle is uniquely measured based on the distance to thepreceding vehicle acquired in step S702 and the V-direction coordinateson the image of the upper end of the preceding vehicle projected in theimage captured by the camera 10.

Next, step S704 is executed. Step S704 is a step in which the mainprocessor 40 acquires the coordinates of the landmark 63 that is assumedto exist within the angle of view from the map information. The mainprocessor 40 identifies the area where the vehicle exists from the roughposition of the own vehicle specified in step S700, and reads the maptile corresponding to the area. Then, the coordinates of the landmark 63recorded on the map tile are acquired. Here, the landmark 63 includes awhite line (in other words, a lane mark). Alternatively, it may be moreeffective when it is a target that is difficult to image with the camera10 due to the large size of the preceding vehicle, and it may be moreeffective for a traffic light or a destination indication, a speed limitsign, etc. The coordinates of the landmark 63 include the coordinateinformation of the four corners forming the rectangle, for example, whenthe landmark 63 has a rectangular plate shape orthogonal to thetraveling direction of the vehicle.

Next, step S705 is executed. Step S705 is a step of determining whetheror not the preceding vehicle exists at a position that blocks thelandmark 63 that would be disposed within the angle of view. As shown inFIG. 15, a portion (the hatched portion in FIG. 15) that becomes a blindspot of the camera 10 is determined based on the inter-vehicle distanceacquired in step S702, the vehicle height of the preceding vehicleacquired in step S703, and the angle of view of the camera 10 mounted onthe own vehicle. When the blind spot includes at least a part of thecoordinates constituting the landmark 63, it is determined that thepreceding vehicle blocks the landmark 63, and this step is a “YES”determination. The example shown in FIG. 15 is an example in which allthe landmarks 63 are included in the blind spots created by thepreceding vehicle, and this step is a “YES” determination.

When the determination in step S705 is “YES”, the process proceeds tostep S706. Step S706 is a step in which the main processor 40 controlsthe actuator 70 to change the relative position between the own vehicleand the obstacle so that the landmark 63 can be recognized by the camera10. Specifically, for example, the actuator 70 is a braking device, andthe main processor 40 drives the braking device to brake the ownvehicle.

As shown in FIG. 16, the main processor 40 increases the inter-vehicledistance between the own vehicle and the preceding vehicle so that thelandmark 63 is completely removed from the blind spot portion by thisbraking. Specifically, the vehicle is braked until the vehicle has theinter-vehicle distance such that everything from the upper end to thelower end of the landmark 63 can be visually recognized above the upperend of the preceding vehicle. As will be described later, it may be alsopossible to brake until a part of the landmark 63 can be visuallyrecognized. As a result, the main processor 40 can recognize thelandmark 63, and the coordinates of the landmark 63 can be calculatedbased on the image.

In the map system 1, the landmark 63 can be easily recognized withoutacquiring the vehicle type. This is particularly effective whensufficient time for acquiring the vehicle type of the preceding vehiclecannot be secured due to a sudden interruption or the like, or when anobstacle other than the vehicle suddenly jumps in front of the vehicle.

The actuator 70 controlled by the main processor 40 may not be limitedto the braking device, and may be, for example, a steering operation.Specifically, when the preceding vehicle is a tall vehicle, the mainprocessor 40 may control the steering to change lanes to create asituation in which there is no preceding vehicle that becomes anobstacle in front of the own vehicle. Various controls such asdeceleration, lane change, and position change in the lane can beadopted as vehicle control (hereinafter, detection rate improvementcontrol) for facilitating the detection of landmarks by the peripheralmonitoring sensor. The detection rate improvement control corresponds tothe control for reducing the possibility that the landmark cannot berecognized continuously.

Further, an example of determining that the preceding vehicle isblocking the landmark 63 when the blind spot of the preceding vehicleincludes a part of the landmark 63 has been described. Alternatively,even when a part of the landmark 63 can be visually recognized outsidethe blind spot, it may be determined that the preceding vehicle does notblock the landmark 63. Alternatively, these determination criteria maybe variable depending on the type of landmark 63.

When the own vehicle is equipped with a plurality of peripheralmonitoring sensors and at least one of the plurality of peripheralmonitoring sensors can capture the landmark, the vehicle control forfacilitating the peripheral monitoring sensor to detect the landmarkeasily may not be carried out. For example, even when the precedingvehicle is a tall vehicle or the preceding vehicle is located at aposition that blocks the landmark in front of the own vehicle, in a casewhere the landmark behind the vehicle can be imaged by the rear camera,it may be configured not to carry out vehicle control such as expansionof inter-vehicle distance or lane change.

Further, the case of implementing the detection rate improvement controlmay not be limited to the case where the preceding vehicle is a tallvehicle or the case where the landmark in front of the own vehicle isblocked by the preceding vehicle. More specifically, it may beconfigured to execute the detection rate improvement control when theinter-vehicle distance to the preceding vehicle is less than apredetermined distance (for example, 20 meters). This configurationcorresponds to a configuration in which detection rate improvementcontrol is executed when a preceding vehicle as an obstacle exists in apredetermined region (here, an region within 20 meters in front of thevehicle) within the imaging range of the camera 10. Further, when theangle formed by the straight line from the camera 10 toward the upperend of the rear surface of the preceding vehicle with respect to theroad surface (hereinafter, the looking-up angle θ) is equal to or higherthan a predetermined threshold value (for example, 15 degrees), thedetection rate improvement control such as deceleration or the like maybe performed. When the ratio occupied by the portion corresponding tothe preceding vehicle in the image frame is equal to or more than apredetermined threshold value (for example, 30% or more), the detectionrate improvement control such as deceleration may be executed.

In addition, in a case where the vehicle is traveling in a section wherethe landmark should be observed, when the landmark detection fails for apredetermined number of times (for example, 5 times) or for apredetermined time interval (for example, 3 seconds) continuously, itmay be configured to execute the detection rate improvement control.Further, it may be configured to execute the detection rate improvementcontrol when the detection success rate for the landmark that should beoriginally observed becomes less than a predetermined threshold value.The detection success rate may be expressed by the ratio of the numberof attempts to detect the landmark within a certain period of time tothe number of successful detections.

The conditions for executing the detection rate improvement control canbe changed as appropriate. In addition, the main processor 40 may beconfigured to acquire the current position of the other vehicle and theperipheral image acquired by the other vehicle from the other vehicle byvehicle-to-vehicle communication as the detection rate improvementcontrol. According to such a configuration, the main processor 40 candetect landmarks based on peripheral images provided by other vehicles.In addition, the own vehicle can be indirectly localized based on theposition information of the landmark, the position information of theother vehicle, and the relative position of the own vehicle with respectto the other vehicle.

Further, the main processor 40 may be configured to acquire thelocalization result (that is, detailed position information of the othervehicle) of the other vehicle (for example, the preceding vehicle) byvehicle-to-vehicle communication as the detection rate improvementcontrol. According to such a configuration, the main processor 40indirectly localizes the subject vehicle based on the detailed positioninformation of the other vehicle (hereinafter referred to as thereference vehicle) that provides the localization result as a provisionsource and the relative position of the own vehicle with respect to thereference vehicle. The relative position of the own vehicle with respectto the reference vehicle may be specified based on the detection resultof the peripheral monitoring sensor such as the camera 10.

Further, the main processor 40 normally performs localization usinglandmarks existing in front of the own vehicle (in other words, using afront camera image). On the other hand, when the field of view of thefront camera is obstructed by the preceding vehicle, the localizationmay be performed using the image of the rear camera as the rearmonitoring device. That is, as the detection rate improvement control,the peripheral monitoring sensor used for detecting the landmark may bechanged. Changing the number and combination of peripheral monitoringsensors used to detect landmarks is also an example of detection rateimprovement control.

The above control may be configured to be executed on condition that theown vehicle is traveling on a predetermined road (for example, a generalroad). On general roads, the distance between vehicles and othervehicles is shorter than when driving on highways, and therefore, it maybe difficult to view landmarks. Therefore, the above control may be moreuseful when driving on a general road than when driving on a highway.Further, from the opposite viewpoint, the main processor 40 may beconfigured not to execute the above control when the traveling roadcorresponds to a predetermined road type (for example, anautomobile-only road).

It may be low possibility that other vehicles will make it difficult todetect landmarks while driving on motorways such as highways. The loadon the main processor 40 can be reduced by canceling the detection rateimprovement control while traveling on the motorway.

In addition, the main processor 40 may be configured to set the ACCdistance longer when the map utilization function is enabled than whenthe map utilization function is not enabled. According to thisconfiguration, the risk of difficulty in detecting landmarks can befurther reduced.

[Operations in Dark Environment Such as at Night]

The situation in which the coordinates of the landmark 63 are difficultto specify may not be limited to the case where there is an obstacle inthe vicinity of the own vehicle that obstructs the imaging of thelandmark 63. For example, even when the surrounding environment of thevehicle is relatively dark, such as in a tunnel or at night, it may bedifficult for the camera 10 to detect the landmark 63 and calculate thecoordinates.

The map system 1 may be configured to facilitate the detection oflandmarks 63 and the calculation of coordinates even when thesurrounding environment of the vehicle is relatively dark, and thus tomore accurately identify the position of the own vehicle.

Hereinafter, the operation of the map system 1 based on such a technicalidea will be described with reference to FIG. 17. Here, as an example,the control of a headlight installed to irradiate the illumination lightin front of the vehicle will be described as an example. In addition tothe light that illuminates the front of the vehicle, the light thatilluminates the rear of the vehicle and the side of the vehicle maycoexist, and the object of control may be the light that illuminates therear of the vehicle and the side of the vehicle.

As shown in FIG. 17, first, step S800 is executed. Step S800 is a stepof determining whether or not an application that uses map informationis being started. The application that uses the map information is, forexample, automatic steering realized by checking the coordinates of thelandmark 63 calculated based on the image with the map information andspecifying the position of the own vehicle. When the application thatuses the map information is not executed, this step is judged as “NO”,and this flow ends. When the application is executed, this step isdetermined to be “YES”, and the process proceeds to step S801.

Step S801 is a step of determining whether or not the control of theheadlight in the vehicle is set to the automatic mode. The automaticmode is set to a state in which light distribution control such asup/down or left/right of the headlight is automatically set, forexample, an active high beam system (AHS). When the headlight control isin the manual mode, this step is judged as “NO” and this flow ends. Onthe other hand, when the headlight control is in the automatic mode,this step is a YES determination and the process proceeds to step S802.

Step S802 is a step in which the main processor 40 determines whether ornot the brightness of the surrounding environment of the vehicle isequal to or less than a predetermined threshold value. Specifically, theilluminance detected by the illuminance sensor mounted on the vehicle iscompared with a predetermined threshold value. When the illuminance islarger than the threshold value, it is determined that it is not alwaysnecessary to turn on the headlights, so that this step is determined tobe “NO” and the present flow ends. On the other hand, when theilluminance is equal to or less than the threshold value, the processproceeds to step S803 to turn on the headlight.

Next, step S804 is executed. Step S804 is a step in which the mainprocessor 40 determines whether or not there is a preceding vehicle oran oncoming vehicle with respect to the own vehicle. For example, thepresence of the preceding vehicle is recognized by detecting the lightof the rear light from the image captured by the camera 10.Alternatively, the presence of the preceding vehicle is recognized bythe fusion configuration of the camera 10 and the radar or LIDAR.Further, the presence of the oncoming vehicle is recognized by detectingthe light of the headlight from the image captured by the camera 10, forexample. Alternatively, the presence of the oncoming vehicle isrecognized by the fusion configuration of the camera 10 and the radar orLIDAR.

When the presence of an oncoming vehicle or a preceding vehicle isdetected in step S804, this step is determined to be “YES” and theprocess proceeds to step S805. Step S805 is a step of setting theirradiation mode of the headlight to the low beam. In the low beam mode,in order to suppress the glare of the driver of the preceding vehicle orthe oncoming vehicle, the irradiation direction of the head light iscontrolled such that the headlights are irradiated so as not to directlyirradiate the corresponding vehicle at least in the direction in whichthe preceding vehicle or the oncoming vehicle exists.

After that, step S806 is executed. Step S806 is a step in which the mainprocessor 40 controls the light distribution of the headlights so as toselectively irradiate the illumination light in the direction in whichthe landmark 63 is assumed to be present. As an example, as shown inFIG. 18, it is assumed that a preceding vehicle and an oncoming vehicleexist on an oncoming two-lane road traveling on the left side. At thistime, the main processor 40 controls the headlight, which is theactuator 70, to maintain the headlight on the right side of the vehiclewith a low beam so that the oncoming lane side in which the oncomingvehicle travels is not excessively irradiated with the illuminationlight. On the other hand, the light distribution of some light sourcesof the headlights on the left side of the vehicle is controlled so thatthe preceding vehicle is not excessively illuminated, and the low beamis maintained for the irradiation around the preceding vehicle. Further,the light distribution of a part of the light source of the headlight onthe left side of the vehicle is controlled to be high beam so that theillumination light of the headlight is irradiated outside the lane wherethe mark 63 should be present, that is, outside the lane including theroad shoulder on the lane side on which the own vehicle travels. As aresult, it is possible to irradiate the illumination light of theheadlight in the direction in which the presence of the landmark 63 isassumed while suppressing the glare of the driver of the oncomingvehicle or the preceding vehicle. According to this, the detectionfrequency of the landmark 63 is increased, and the calculation frequencyof the coordinates of the landmark 63 from the image is also improved.Therefore, it is possible to collate with the coordinates of thelandmark 63 held by the map information for a longer period of time, sothat the position of the own vehicle can be specified more accurately.

When the presence of an oncoming vehicle or a preceding vehicle is notdetected in step S804, this step is determined to be “NO” and theprocess proceeds to step S807. Step S807 is a step of setting theirradiation mode of the headlight to the high beam. In the high beammode, since there are no preceding vehicles or oncoming vehicles aroundthe own vehicle, the headlight irradiation direction is adjusted so thata distant field can be visually recognized.

After that, step S808 is executed. Step S808 is a step in which the mainprocessor 40 controls the light distribution of the headlights so as toselectively irradiate the illumination light in the direction in whichthe landmark 63 is assumed to be present. In this step, for example,wide light distribution or distant light distribution can be adopted forthe light distribution of the headlights. The wide light distribution isa light distribution mode that illuminates a wider area than theirradiation range in the left-right direction in the high beam or thehigh beam. As a result, the landmark 63 outside the lane including theroad shoulder can be detected more easily. Further, the distant lightdistribution is a light distribution mode in which the illuminationlight is concentrated farther than the high beam and reaches the distantarea when traveling at high speed. As a result, the landmark 63 such asthe destination sign can be detected more easily even when traveling athigh speed.

In the above map system 1, an example of implementing a lightdistribution that is easy to detect the landmark 63 is described on thecondition that the light control is in the automatic mode.Alternatively, in a case where the light control may not be automaticand the driver operates the light, when the headlights are set to lowbeam and the illuminance of the environment around the vehicle is belowa predetermined threshold, the map system 1 suggests the driver tochange the light distribution of the headlights to high beam. Proposalsfor changing the light distribution can be made by, for example,displaying it on the HMI 60 or transmitting it by a voice message.

At night, it may be difficult to recognize landmarks that are notprovided with lighting or the like from the captured image of the camera10. Therefore, during the daytime, localization is performed based onvarious landmarks, while at night, it may be preferable that thelandmarks used for localization are limited to internal lighting signs,signs with street lights and other lights arranged nearby, trafficlights, and electric bulletin boards and the like. An internallyilluminated sign refers to a sign in which a light source is providedinside a sign board. It may be preferable that the map data includeswhether or not it can be detected even at night as the attributeinformation of the landmark. Whether or not it can be detected even atnight may be set based on the probe data at night. For example, alandmark detected with a predetermined probability in probe datacollected at night may be set as a landmark that can be recognized evenat night.

[Method for Downloading Map Tiles]

The download of the map information from the server 3 needs to beexecuted within the limited communication band between the server 3 andthe vehicle, and efficient communication is required. Here, a map system1 that can efficiently and completely download map tiles related to thedownload of map information will be described.

This map system 1 realizes the download of map tiles in different flowsdepending on whether or not the destination to which the vehicle travelsis set. Hereinafter, the case where the destination is not set and thecase where the destination is set will be described.

<Destination is not Set>

A specific flow will be described with reference to FIGS. 19 and 20. Asshown in FIG. 19, first, step S900 is executed. Step S900 is a step inwhich the main processor 40 identifies a rough position of the ownvehicle by GPS or the like. By this step, the area where the own vehicleexists is grasped. The series of processes illustrated in FIG. 19 may bestarted with the turning on of the traveling power source as a trigger.In addition, the series of processes illustrated in FIG. 19 may bestarted when the map utilization function or the automatic drivingfunction is activated.

Next, step S901 is executed. Step S901 is a step in which the mainprocessor 40 downloads the map tile corresponding to the area where theown vehicle exists. The main processor 40 requests the server 3 todistribute the map data of the map tile corresponding to the position ofthe own vehicle. For example, the main processor 40 transmits the tileID of the area, to which the own vehicle position belongs, to the server3. The server 3 delivers the map tiles requested by the vehicle. Whenthe server 3 does not have the map data of the requested area (forexample, when the expiration date has expired), the server 3 returns asignal indicating that it does not have the map data of the requestedarea. For example, a signal in which an invalid value (for example,“Null”) is set at a predetermined position in the data format isreturned.

Here, as an example, the map data may not exist in the memory 80 whenthe running power is turned on. In the configuration in which the mapdata is left in the memory 80, step S901 may be omitted when the maptile corresponding to the area where the own vehicle exists is stored inthe memory 80. Further, here, as an example, necessary map data isspecified from the vehicle side and requested to the server 3.Alternatively, the distribution mode of the map data may not be limitedto this mode. The vehicle may be configured to transmit the currentposition to the server 3, and the server 3 determines map datacorresponding to the reported vehicle position and distributes the mapdata to the vehicle.

FIG. 20 shows an example of map tiles. In FIG. 20, 80 map tiles areshown. A unique ID is assigned to each of the map tiles stored in theserver 3, but here, for convenience, 25 map tiles are assigned serialcodes a to y. Here, when the rough position of the own vehicle specifiedin step S900 is the rhombus shown in FIG. 20, the map tile defined as mcorresponds to the first tile. Hereinafter, the map tile correspondingto the area where the own vehicle exists is particularly referred to asthe first tile.

Next, step S902 is executed. Step S902 is a step in which the mainprocessor 40 divides the first tile into sub tiles. As shown in FIG. 20,the main processor 40 is set to divide the map tile m, which is thefirst tile, into four square regions and execute the subsequentprocessing.

Next, step S903 is executed. Step S903 is a step in which the mainprocessor 40 identifies the sub tile to which the own vehicle belongsfrom among the plurality of sub tiles. In the example shown in FIG. 20,the own vehicle belongs to the upper right sub tile in the divided maptile m.

Next, step S904 is executed. Step S904 is a step of designating a maptile adjacent to the sub tile to which the own vehicle belongs as adownload target. In the example shown in FIG. 20, the first tile is themap tile m, and the sub tile to which the own vehicle belongs is the subtile located in the upper right. Therefore, the map tiles designated asdownload targets in step S904 are the map tiles h, i, and N. The maptile adjacent to the sub tile corresponds to a candidate for the maptile that can be moved next when the vehicle moves across the map tile.In other words, the map tile adjacent to the sub tile corresponds to themap tile that the vehicle may pass through. From one viewpoint, a maptile existing at a position where a vehicle can enter within apredetermined time (for example, 0.5 hours) may correspond to a map tilein which a vehicle is relatively likely to pass. In addition, map tilesthat exist within a predetermined distance from the current position ofthe vehicle may also be map tiles that the vehicle may pass through.

Next, step S905 is executed. Step S905 is a step of downloading a maptile that is designated as a download target and is not cached in thememory 80 (that is, has not been acquired). As described above, the maptiles h, i, and n correspond to the download targets. When any of thesehas already been downloaded and stored in the memory 80, thecorresponding map tile is not downloaded.

Next, step S906 is executed. Step S906 is a step of caching thedownloaded map tiles in the memory 80. The cached map tile can be usedwithout downloading as long as the corresponding data remains in thememory 80.

Next, step S907 is executed. Step S907 is a step of determining whetheror not the own vehicle has moved to a second tile different from thefirst tile. For example, when the vehicle moves from the map tile m tothe map tile i, this step is determined to be “YES”. In this example,the map tile i corresponds to the second tile. When the vehiclecontinues to exist in the first tile, the process of step S907 iscontinued. When the determination in this step is “YES”, the processproceeds to step S908.

Step S908 is a step of designating the map tiles around the second tileas the download target. When the vehicle moves from map tile m to maptile i, the second tile is map tile i, and the map tiles specified to bedownloaded are eight map tiles c, d, e, h, j, m, n, and o.

Next, step S909 is executed. Step S909 is a step of downloading a maptile that is designated as a download target and is not cached in thememory 80. As mentioned above, eight map tiles c, d, e, h, j, m, n and oare download targets, but the map tiles h, m and n were alreadydownloaded and cached in the previous step, and therefore, they will notbe downloaded. That is, the number of map tiles to be downloaded in stepS909 is substantially five. Then, as long as the vehicle is continuouslyrunning after the first tile is set, the maximum number of map tiles tobe downloaded after moving to the second tile is five in all situations.That is, even if all the map tiles around the map tile to which thevehicle is disposed are not downloaded, when at most five map tiles aredownloaded, it is possible to surely acquire information on the maptiles that the subject vehicle is expected to move next.

Next, step S310 is executed. Step S310 is a step of caching thedownloaded map tiles in the memory 80. The cached map tile can be usedwithout downloading as long as the corresponding data remains in thememory 80.

Next, step S311 is executed. Step S310 is a step in which the mainprocessor 40 determines whether or not an application that requires mapinformation is being executed. An application that requires mapinformation is an application related to map utilization, such asautomatic steering control while specifying the position of the ownvehicle. While the application that requires map information isactivating, it is necessary to continue to download the map tile at thedestination where the vehicle is traveling, and the flow from step S907to step S311 is repeated. That is, the map tiles around the destinationmap tile are set as download candidates, and the uncached map tiles arecontinuously downloaded. On the other hand, when the application thatutilizes the map information is stopped and the application is notactivated at the time of executing step S311, this flow ends.

In the above example, an example is described such that the vehiclemoves from the initial sub tile in the first tile to which the vehicleis disposed initially to the second tile directly without moving toanother sub tile in the first tile. Alternatively, another example willalso be briefly described.

For example, the map tile m is the first tile, and the vehicle existingin the upper right sub tile has moved to the lower right sub tile of thesame first tile. In this case, in step S904, the map tiles as downloadtargets are the map tiles h, i, and n when the vehicle is located in theupper right sub tile, and the map tiles n, r, and s when the vehiclemoves to the lower right sub tile. When the vehicle subsequently movesto the map tile r, the map tiles to be downloaded in step S909 are fivemap tiles I, q, v, w, and x.

As described above, by adopting the map system 1 of the presentdisclosure, it is possible to comprehensively download the map tilescorresponding to the area where the vehicle is expected to travel withthe minimum number of downloads. In the above configuration, as adownload policy when the destination is not set after the power fordriving the vehicle is turned on, three map tiles adjacent to the subtile to which the own vehicle belongs among the sub tiles obtained bydividing the first tile into four and the first tile are set as thedownload targets. The above process related to map download may betriggered by the activation of the automatic driving function or theactivation of the map utilization function based on the user input tothe HMI 60 after the driving power source is turned on. The first tile,on one aspect, is a map tile that corresponds to the position of thevehicle at the time the running power is turned on. In another aspect,the first tile corresponds to the map tile to which the vehicle positionbelongs at the time when the automatic driving function is activated orwhen the map utilization function is activated.

<Case where Destination is Set>

Next, the flowchart when the destination is set will be specificallydescribed with reference to FIGS. 21 and 22.

As shown in FIG. 21, first, step S920 is executed. Step S920 is a stepin which the main processor 40 identifies a rough position of the ownvehicle by GPS or the like. By this step, the area where the own vehicleexists is grasped. In the example shown in FIG. 22, the position of theown vehicle is indicated by a point A (i.e., a black-painted rhombus).

Next, step S921 is executed. Step S921 is a step of acquiring the globalcoordinates of the set destination. The destination can be set by anactive instruction of the driver who is a user, an automatic settingfrom an external instruction system, or other means. Further, inaddition to the operation by the car navigation system mounted on thevehicle, the destination may be set by the map system 1 receiving thedestination set by the mobile communication device. In the example shownin FIG. 22, the destination is indicated by a point B (i.e., a whitediamond).

Next, step S922 is executed. Step S922 is a step of calculating the mainroute L based on the position of the own vehicle specified in step S920and the coordinates of the destination acquired in step S921. The mainroute L is a travel route recommended for the own vehicle to move fromthe current position to the destination so as to satisfy the specifiedconditions. In the example shown in FIG. 22, it is shown as a solid lineconnecting the current position A and the destination B.

Next, step S923 is executed. Step S923 is a step of calculating thebranch path R. The branch road R is a route connected to the main routeL, and is a route on which the vehicle may leave the main route L andtravel. The branch path R includes a first branch path R1 that directlybranches from the main path L, and a second branch path R2 that is notdirectly connected to the main path L but branches from the first branchpath R1.

Next, step S924 is executed. Step S924 is a step of designating the maptile to which the main route L and the branch road R belong as thedownload target. All map tiles to which the main route L belongs aredownload targets. On the other hand, for the map tile to which thebranch road R belongs, two tiles that are the map tile to which thebranch road R belongs and are continuous from the map tile to which themain route L belongs are designated as download targets. Regarding themap tiles related to the branch road R, the number of tiles continuousfrom the map tile to which the main route L belongs may not be limited,and the number of two tiles may be one example. In the example shown inFIG. 22, the map tile to be downloaded is hatched.

Next, step S925 is executed. Step S925 is a step of downloading a maptile that is designated as a download target and is not cached in thememory 80. When there is a map tile that has been downloaded in the pastand stored in the memory 80, the corresponding map tile may not bedownloaded.

Next, step S926 is executed. Step S926 is a step of caching thedownloaded map tiles in the memory 80. The cached map tile can be usedwithout downloading as long as the corresponding data remains in thememory 80.

By going through the above steps, it is possible to appropriately selectthe map tiles to be downloaded for the main route from the currentposition to the destination and the branch road that may travel awayfrom the main route.

It may be preferable to set the download priority for a plurality of maptiles designated as download targets. For example, the closer the maptile is to the map tile to which the vehicle belongs, the higher thedownload priority is set. As a result, the map tiles are downloaded inthe order of arrival of the map tiles, so that the map tiles can beefficiently downloaded without omission while effectively utilizing thecommunication band.

Further, the map tile to which the main route L belongs may bepreferentially downloaded as compared with the map tile to which thebranch road R belongs. Since the vehicle has a higher probability oftraveling on the main route L than the branch road R, the map tiles canbe efficiently downloaded while effectively utilizing the communicationband.

Further, when there is an area in which it is known in advance that thecommunication state between the vehicle and the server 3 deterioratesamong the routes where the vehicle is predicted to travel and includesthe main route L and the branch road R, the priority may be given todownloading corresponding map tiles. For example, when it is expected totravel in a difficult communication section such as a mountainous areaor a tunnel where the communication condition deteriorates, whiletraveling in an urban area where the communication condition is good,the map tiles corresponding to the mountainous area/tunnel section (thatis, the communication difficult section) may be downloaded in advance.The download priority may be set higher in the order of, for example,the map tile corresponding to the current position (that is, the firsttile), the map tile adjacent to the first tile and the main route passesthrough, and the communication difficulty section.

Although some examples of prioritizing the map tiles to be downloadedhave been described above, it may not be limited to these examples.Further, the priority may be set by appropriately combining theseconditions.

Further, regarding the map tiles specified as the download target, anexample of downloading the map tiles corresponding to both the mainroute L and the branch road R has been described. Alternatively, asystem for downloading the map tiles corresponding to only the mainroute L may be used. Further, it is not necessary to adopt all theroutes connected to the main route L as the branch road R. A narrowstreet connected to the main route may not be adopted as a branch roadR. Further, among the roads connected to the main route L, a road havingthe same rank or higher as the road constituting the main route may beset as the branch road R. A road having the same rank as a certain roadmeans, for example, a road having the same road type (national roads,state roads, narrow streets). For state roads, roads of the same rank orhigher refer to national roads and state roads. In the United States,road types may be divided into interstate highways, US highways, stateroads, and municipal roads in descending order of road rating. Further,a road having the same number of lanes as the main route or more may beadopted as a road of the same rank or higher. Whether or not to adoptthe road connected to the main route as the branch road R may bedetermined by comparing the road scale of the main route near theconnection point (e.g., substantially an intersection) with the scale ofthe connecting road. The road scale corresponds to the above-mentionedroad rating and number of lanes.

Furthermore, in the above, when the destination is set, theconfiguration for systematically downloading the map tile in which theown vehicle is likely to pass on the road is disclosed. Alternatively,it may not be limited to this feature. Even when the destination is notset, the map tile through which the own vehicle travel path goes may beset as the download target. More specifically, among the map tilesthrough which the vehicle travel path passes, a predetermined number(for example, 3) of map tiles existing on the vehicle travelingdirection side from the current position may be set as download targets.According to such a configuration, even when the destination is not set,the map tile in which the own vehicle is likely to pass on the road maybe downloaded in advance as in the case where the destination is set.

The planned map tile download method described above may only be appliedto static map data. All the dynamic map data of the map tiles that thevehicle is likely to pass through may be downloaded at once. This isbecause the amount of dynamic map data may be expected to be smallerthan that of static map information. Further, the main processor 40 maybe configured to change the timing and rules for downloading the dataaccording to the types such as static information and dynamicinformation. For example, the dynamic map data may be sequentiallydownloaded in real time, while the static map data may be configured tobe downloaded on a monthly or weekly basis. The various configurationsand methods described above may be applied not only when the vehicle istraveling on a motorway such as an expressway, but also when the vehicleis traveling on an ordinary road.

Here, in the above, the case where the rough position of the own vehiclecan be specified by using GPS or the like within a predeterminedpreparation time (for example, 30 seconds) after the power for travelingis turned on has been described. However, in reality, it may not bealways possible to specify the position of the own vehicle within apredetermined preparation time after the power for traveling is turnedon. When the vehicle is parked in a place where GPS radio waves do notenter, such as an underground parking lot, it may be difficult tospecify the position coordinates of the own vehicle. In view of suchcircumstances, when the vehicle is parked (for example, when the shiftposition is set to the parking position), it may be preferable that themain processor 40 may set the own vehicle position coordinates specifiedat that time to the storage unit 82 or the like. According to thisconfiguration, even when the vehicle is parked in a place where GPSradio waves do not reach, the location information recorded in thestorage unit 82 can be referred to roughly determine the position of thevehicle at the timing when the driving power is turned on. As a result,the first tile can be specified.

When the automatic driving function that can be executed is restricteddue to the condition of the vehicle and the external environment, theuser may be notified via the HMI 60, for example, by displaying an iconon the display. For example, when the position of the own vehicle cannotbe specified or the map data cannot be acquired, the main processor 40notifies the occupants that the automatic driving function of levelthree or higher cannot be executed via the HMI 60. In the above, thecase where the map data is configured to be distributed in map tileunits has been illustrated. Alternatively, the same feature may beapplied to the case where the map data is configured to be distributedin patch units. That is, it can be implemented by replacing the abovemap tile with a patch or a patch-corresponding area.

[Modifications of the Vehicle Side System Configuration]

The configuration of the in-vehicle system 2 constituting the map system1 may not be limited to the configuration shown in FIG. 2. For example,as shown in FIG. 23, the in-vehicle system 2 may be realized by usingthe front camera module 90, the locator 100, the Ethernet switch 110,and the communication module 50. “Ethernet” is a registered trademark.Further, in FIG. 23, the sensor 30 and the HMI 60 are not shown.

The front camera module 90 includes a camera body 91, a camera processor92, and a memory (not shown). The camera body 91 has a configurationcorresponding to the above-mentioned camera 10. The camera processor 92corresponds to the image processor 20. Further, as a more preferableembodiment, the camera processor 92 is configured to be capable ofperforming position calculation (that is, localization) using the imagerecognition result and the map data in a complementary manner. Inaddition, the camera processor 92 has a function of controlling thevehicle (for example, steering control) by using at least one of theimage recognition result and the map data. The front camera module 90sequentially (for example, every 100 milliseconds) provides the locator100 with data of feature information and vehicle information (forexample, current position, yaw rate, and the like) as a result of imagerecognition. Data communication between the front camera module 90 andthe locator 100 may be realized by CAN (Controller Area Network:registered trademark), FlexRay (registered trademark), Ethernet(registered trademark), USB, UART, or the like.

The locator 100 is a device that identifies the current position usingthe map data provided by the server 3. The locator 100 includes alocator processor 101, a volatile memory 102, and a non-volatile memory103. The locator 100 has a function as a positioning sensor 30 a. Thelocator processor 101 sequentially acquires the image recognition resultand the vehicle information provided from the front camera module 90,and uploads them to the server 3 as probe data. Further, the locator 100downloads map data according to the position of the own vehicle from theserver 3 via the communication module 50 or the like, and stores the mapdata in the non-volatile memory 103. Such a locator 100 corresponds toan ECU that performs processing related to transmission/reception of mapdata in one aspect.

The locator 100 sequentially expands the data of the section related tothe traveling of the own vehicle among the maps downloaded from theserver 3 into the volatile memory 102, and sequentially provides thedata to the front camera module 90. The developed map data around theown vehicle is used for localization and steering control by the frontcamera module 90. The localization and steering control may beconfigured to be executed by the locator 100 instead of the front cameramodule 90. The arrangement of the functions provided in eachconfiguration can be changed as appropriate.

The section in which the own vehicle travels refers to a road within apredetermined distance from the current position, for example, in thedirection of travel of the own vehicle (basically forward). Thepredetermined distance here is a parameter that defines the readingrange of the map data, and is, for example, 200 meters. The readingrange may be 100 meters in front of the own vehicle, 400 meters, 500meters, or the like. The reading range may be adjusted according to thevehicle speed and the type of travel path. For example, the faster thevehicle speed, the longer the read range is set. Further, when thetraveling road is an expressway, the reading range may be set longerthan when the traveling road is a general road. For convenience, localmap data including detailed road shape information (curvature, gradient,width, and the like) within a predetermined distance ahead of the ownvehicle is referred to as forward map data. The forward map datacorresponds to the map data around the current position.

The locator 100 is connected to the communication module 50 via, forexample, an Ethernet switch 110. Further, the locator 100 is connectedto the automatic operation ECU, the body ECU, the operation supportdevice, and the like so as to be able to communicate with each other viathe Ethernet switch 110 or directly. In the configuration shown in FIG.23, the locator 100 controls the transmission and reception of map dataoverall. Further, according to the configuration shown in FIG. 23, theprocessing that the main processor 40 is in charge of is shared by theimage processor 20 and the locator processor 101. Therefore, the load oneach processor can be reduced.

The image frame captured by the front camera module 90 may be configuredto be output to the multimedia ECU as a continuous video signal. Thevideo signal may be transmitted in a predetermined format such as LVDS(Low voltage differential signaling). Further, the Ethernet switch 110existing between the locator 100 and the communication module 50 may bean arbitrary element. The locator 100 and the communication module 50may be directly connected by a USB cable or the like. In addition, thelocator 100 may be provided by using a navigation ECU or a multimediaECU. The navigation ECU is an ECU that executes map display and routeguidance processing for occupants. The multimedia ECU is an ECU thatprovides functions such as audio, video reproduction, and web browsing.According to the configuration in which the map datatransmission/reception and management functions are added to theexisting ECU, the system introduction cost can be reduced.

Further, in the in-vehicle system 2, the system for downloading map datafrom the server 3 and the system for uploading probe data to the server3 may be separated. For example, in the example shown in FIG. 24, themultimedia ECU 120 acquires the image recognition result and the vehicleinformation from the front camera module 90, packages them as probedata, and uploads them to the server 3 via the communication module 50.That is, the multimedia ECU 120 controls the upload of the probe data tothe server 3. Further, in the configuration shown in FIG. 24, thelocator 100 downloads the map data from the server 3 via thecommunication module 50, and sequentially provides the front map data tothe front camera module 90 via the driving support device 130. That is,the locator 100 controls the map download. The driving support device130 sequentially provides the front map data provided by the locator 100to the front camera module 90.

Further, when it becomes difficult to continue the automatic drivingcontrol by the front camera module 90, the driving support device 130automatically travels the vehicle for a predetermined time/apredetermined distance by using the front map data instead of the frontcamera module 90. According to the above configuration, robustnessagainst system abnormality can be enhanced.

[Addition]

The disclosure in this specification and drawings etc. is not limited tothe exemplified embodiment. The disclosure encompasses the exemplifiedembodiments and modifications by those skilled in the art based thereon.For example, the present disclosure is not limited to the combinationsof components and/or elements shown in the embodiments. The presentdisclosure may be implemented in various combinations. The presentdisclosure may have additional portions that may be added to theembodiments. The present disclosure encompasses omission of componentsand/or elements of the embodiments. The present disclosure encompassesthe replacement or combination of components and/or elements between oneembodiment and another. The disclosed technical scope is not limited tothe description of the embodiment. Several technical scopes disclosedare indicated by descriptions in the claims and should be understood toinclude all modifications within the meaning and scope equivalent to thedescriptions in the claims.

The control and the method therefor which have been described in thepresent disclosure may be implemented by a special purpose computerprogrammed to execute one or more functions executed by computerprograms. Also, the device and the method therefor which have beendescribed in the present disclosure may be also realized by a specialpurpose hardware logic circuit. Alternatively, the device and the methoddescribed in the present disclosure may be implemented by one or morespecial purpose computers configured by a combination of a processorexecuting a computer program and one or more hardware logic circuits.The computer programs may be stored, as instructions to be executed by acomputer, in a tangible non-transitory computer-readable storage medium.

The control unit here refers to various processors such as the mainprocessor 40, the image processor 20, the server processor 31, thecamera processor 92, the locator processor 101, and the multimediaprocessor 121. Software stored in a tangible memory and a computerexecuting the software, only the software, only hardware, or combinationof them may be possible to provide a method and/or function provided bythe above described various processors. A part or all of the functionsincluded in the communication microcomputer 123 may be realized ashardware. A configuration in which a certain function is implemented ashardware includes a configuration in which the function is implementedby using one or more ICs or the like. As the processor, variousprocessors such as a CPU, an MPU (Micro Processor Unit), a GPU (GraphicsProcessing Unit), and a data flow processor (DFP: Data Flow Processor)can be adopted. Further, one device (for example, the front cameramodule 90) may be realized by combining a plurality of types ofprocessors such as a CPU, MPU, GPU, and DFP. Further, for example, someof the functions to be provided by the main processor 40 may be realizedby using an FPGA (Field-Programmable Gate Array), an ASIC (ApplicationSpecific Integrated Circuit), or the like.

DESCRIPTION OF REFERENCE NUMERALS

-   -   1 indicates Map system, 2 indicates In-vehicle system (vehicle        side device, vehicle control device), 3 indicates Server, 31        indicates Server processor, 10 indicates Imaging device (camera,        peripheral monitoring sensor), 20 indicates Image processor, 30        indicates Status acquisition unit (Sensor), 40 indicates Main        processor, 50 indicates Communication module, 60 indicates HMI,        62 indicates a road segment, 70 indicates Actuator, 80 indicates        Memory, 90 indicates Front camera module, 100 indicates Locator,        110 Ethernet switch, 120 indicates Multimedia ECU, and 130        indicates Driving support device.

The controllers and methods described in the present disclosure may beimplemented by a special purpose computer created by configuring amemory and a processor programmed to execute one or more particularfunctions embodied in computer programs. Alternatively, the controllersand methods described in the present disclosure may be implemented by aspecial purpose computer created by configuring a processor provided byone or more special purpose hardware logic circuits. Alternatively, thecontrollers and methods described in the present disclosure may beimplemented by one or more special purpose computers created byconfiguring a combination of a memory and a processor programmed toexecute one or more particular functions and a processor provided by oneor more hardware logic circuits. The computer programs may be stored, asinstructions being executed by a computer, in a tangible non-transitorycomputer-readable medium.

It is noted that a flowchart or the processing of the flowchart in thepresent application includes sections (also referred to as steps), eachof which is represented, for instance, as S100. Further, each sectioncan be divided into several sub-sections while several sections can becombined into a single section. Furthermore, each of thus configuredsections can be also referred to as a device, module, or means.

While the present disclosure has been described with reference toembodiments thereof, it is to be understood that the disclosure is notlimited to the embodiments and constructions. The present disclosure isintended to cover various modification and equivalent arrangements. Inaddition, while the various combinations and configurations, othercombinations and configurations, including more, less or only a singleelement, are also within the spirit and scope of the present disclosure.

What is claimed is:
 1. A method for generating or updating map dataincluding coordinate information of a plurality of landmarks disposedalong a road, executed in collaboration with a vehicle-side device in avehicle and a server that manages the map data, the method comprising:by the vehicle-side device, uploading index information, indicating thatthe map data needs to be updated to the server in associated with a roadsegment in which the vehicle is traveling when a predetermined eventoccurs in a situation where the vehicle is traveling; by the server,determining whether the map data for the road segment needs to beupdated based on the index information provided by the vehicle-sidedevice; and by the server, setting an update flag indicating that themap data needs to be updated for the road segment when determining thatthe map data needs to be updated.
 2. The method according to claim 1,further comprising: by the vehicle-side device, acquiring a peripheralobject data, representing a feature disposed in a vicinity of thevehicle, from a peripheral monitoring sensor mounted on the vehicle; bythe vehicle-side device, analyzing the peripheral object data tocalculate the position of the landmark with respect to the vehicle; bythe vehicle-side device, calculating a position of the vehicle as afirst position, which is determined based on the position of thelandmark calculated from the peripheral object data and the map datastored in the server; by the vehicle-side device, calculating theposition of the vehicle as a second position, which is determined by ameans that does not use the map data; and by the vehicle-side device,transmitting information to the server as the index informationindicating that a position misalignment occurs in the map at the secondposition when the first position and the second position deviate fromeach other; and by the server, setting the update flag for a point wherethe position misalignment occurs a predetermined number of times or apredetermined frequency.
 3. The method according to claim 1 furthercomprising: by the vehicle-side device, acquiring a peripheral objectdata, representing a feature disposed in a vicinity of the vehicle, froma peripheral monitoring sensor mounted on the vehicle; by thevehicle-side device, analyzing the peripheral object data to calculatethe position of the landmark with respect to the vehicle; by thevehicle-side device, calculating a position of the vehicle based on theposition of the landmark calculated from the peripheral object data andthe map data stored in the server; by the vehicle-side device,autonomously driving the vehicle based on a current position of thevehicle on the map and the map data around the current position; and bythe vehicle-side device, transmitting position information of a pointwhere an operation intervention occurs and information indicating thatthe operation intervention occurs, as the index information to theserver when an occupant of the vehicle executes the operationintervention while executing a process for automatically driving thevehicle using the map data; and by the server, setting the update flagfor the point where the operation intervention occurs with apredetermined operation amount or a predetermined frequency.
 4. Themethod according to claim 1, further comprising: by the server,setting-the update flag at a point where it is publicly disclosed thatthe landmark has moved by a predetermined distance.
 5. The methodaccording to claim 1, further comprising: by the server, acquiring theposition information of the vehicle by wireless communication with thevehicle; and by the server, requesting the vehicle, traveling on theroad segment corresponding to the point where the update flag is set, totransmit the information of the landmark; by the vehicle-side device,analyzing the peripheral object data representing the features disposedaround the vehicle and generated by the peripheral monitoring sensormounted on the vehicle, to specify the position coordinates of thelandmark disposed around the vehicle as observation coordinates; and bythe vehicle-side device, uploading a type of the feature and theobserved coordinates to the server based on a request from the server.6. A vehicle-side device that autonomously drives a vehicle along a roadsegment using map data including coordinate information of a pluralityof landmarks disposed along the road, the vehicle-side devicecomprising: at least one processor, wherein: the processor is configuredto upload index information, indicating that the map data needs to beupdated, to the server in association with a road segment when apredetermined event occurs in a situation that the vehicle is travelingon the road segment using the map data.
 7. The vehicle-side deviceaccording to claim 6, wherein: the at least one processor is configuredto: acquire at least one peripheral object data indicating anenvironment of the vehicle from a peripheral monitoring sensor mountedon the vehicle; analyze the peripheral object data to calculate theposition of the landmark with respect to the vehicle; calculate aposition of the vehicle as a first position, which is determined basedon the position of the landmark calculated from the peripheral objectdata and the map data stored in the server; calculate the position ofthe vehicle as a second position, which is determined by a means thatdoes not use the map data; and transmit information to the server as theindex information indicating that a position misalignment occurs in themap at the second position when the first position and the secondposition deviate from each other.
 8. The vehicle-side device accordingto claim 6, wherein: the at least one processor is configured to:acquire at least one peripheral object data indicating an environment ofthe vehicle from a peripheral monitoring sensor mounted on the vehicle;analyze the peripheral object data to calculate the position of thelandmark with respect to the vehicle; calculate a position of thevehicle based on the position of the landmark calculated from theperipheral object data and the map data stored in the server;autonomously driving the vehicle based on a current position of thevehicle on the map and the map data around the current position; andtransmit position information of a point where an operation interventionoccurs and information indicating that the operation interventionoccurs, as the index information to the server when an occupant of thevehicle executes the operation intervention while executing a processfor automatically driving the vehicle using the map data.
 9. Anon-transitory computer-readable storage medium comprising programinstructions for generating or updating map data including coordinateinformation of a plurality of landmarks disposed along a road, theprogram instructions configured to cause one or more processors at leastto: upload index information, indicating that the map data needs to beupdated, to the server in association with a road segment in which thevehicle is travelling when a predetermined event occurs while thevehicle is traveling.